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2022
[734] Peter Vamplew, Benjamin J. Smith, Johan KšllstrŲm, Gabriel Ramos, Roxana R?dulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley and Cameron Foale. 2022.
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021).
Autonomous Agents and Multi-Agent Systems, 36(2):????. Springer.
DOI: 10.1007/s10458-022-09575-5.
Link: https://doi.org/10.1007/s10458-022-09575...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

The recent paper ‚ÄúReward is Enough‚ÄĚ by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all intelligence, both natural and artificial, and provides a suitable basis for the creation of artificial general intelligence. We contest the underlying assumption of Silver et al. that such reward can be scalar-valued. In this paper we explain why scalar rewards are insufficient to account for some aspects of both biological and computational intelligence, and argue in favour of explicitly multi-objective models of reward maximisation. Furthermore, we contend that even if scalar reward functions can trigger intelligent behaviour in specific cases, this type of reward is insufficient for the development of human-aligned artificial general intelligence due to unacceptable risks of unsafe or unethical behaviour.

[733] Oscar Amcoff. 2022.
I don?t know because I?m not a robot: I don?t know because I?m not a robot:A qualitative study exploring moral questions as a way†to investigate the reasoning behind preschoolers? mental†state attribution to robots.
Student Thesis. 37 pages. ISRN: LIU-IDA/KOGVET-G--22/026--SE.

Portrayals of artificially intelligent robots are becoming increasingly prevalent in children’s culture. This affects how children perceive robots, which have been found to affect the way children in school understand subjects like technology and programming. Since teachers need to know what influences their pupils' understanding of these subjects, we need to know how children’s preconceptions about robots affect the way they attribute mental states to them. We still know relatively little about how children do this. Based on the above, a qualitative approach was deemed fit. This study aimed to (1) investigate the reasoning and preconceptions underlying children’s mental state attribution to robots, and (2) explore the effectiveness of moral questions as a way to do this. 16 children aged 5- and 6 years old were asked to rate the mental states of four different robots while subsequently being asked to explain their answers. Half of the children were interviewed alone and half in small groups. A thematic analysis was conducted to analyze the qualitative data. Children’s mental state attribution was found to be influenced by preconceptions about robots as a group of entities lacking mental states. Children were found to perceive two robots, Atlas, and Nao, differently in various respects. This was argued to be because the children perceived these robots through archetypal frameworks. Moral questions were found successful as a way to spark reflective reasoning about the mental state attribution in the children.

[732] Patrick Doherty and Andrzej Szalas. 2022.
A landscape and implementation framework for probabilistic rough sets using PROBLOG.
Information Sciences, 593(??):546–576. Elsevier Science Inc.
DOI: 10.1016/j.ins.2021.12.062.
Note: Funding Agencies|ELLIIT Network Organization for Information and Communication Technology, Sweden; Swedish Foundation for Strategic Research SSF [RIT15-0097]; Guangdong Department of Science and Technology, China [2020A1313030098]; National Science Centre Poland [2017/27/B/ST6/02018]
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Reasoning about uncertainty is one of the main cornerstones of Knowledge Representation. More recently, combining logic with probability has been of major interest. Rough set methods have been proposed for modeling incompleteness and imprecision based on indiscernibility and its generalizations and there is a large body of work in this direction. More recently, the classical theory has been generalized to include probabilistic rough set methods of which there are also a great variety of proposals. Pragmatic, easily accessible, and easy to use tools for specification and reasoning with this wide variety of methods is lacking. It is the purpose of this paper to fill in that gap where the focus will be on probabilistic rough set methods. A landscape of (probabilistic) rough set reasoning methods and the variety of choices involved in specifying them is surveyed first. While doing this, an abstract generalization of all the considered approaches is derived which subsumes each of the methods. One then shows how, via this generalization, one can specify and reason about any of these methods using PROBLOG, a popular and widely used probabilistic logic programming language based on PROBLOG. The paper also considers new techniques in this context such as the use of probabilistic target sets when defining rough sets and the use of partially specified base relations that are also probabilistic. Additionally, probabilistic approaches using tolerance spaces are proposed. The paper includes a rich set of examples and provides a framework based on a library of generic PROBLOG relations that make specification of any of these methods, straightforward, efficient and compact. Complete, ready to run PROBLOG code is included in the Appendix for all examples considered.

[731] Ulrika ŇkerstrŲm. 2022.
LekmannabedŲmning av ett sjšlvkŲrande fordons kŲrfŲrmŚga: betydelsen av att erfara fordonet i trafiken.
Student Thesis. 31 pages. ISRN: LIU-IDA/KOGVET-G--22/025--SE.

Datorstyrda maskiner som både kan styra sina egna aktiviteter och som har ett stort rörelseomfång kommer snart att dela vår fysiska miljö vilket kommer innebära en drastisk förändring för vår nuvarande mänskliga kontext. Tidigare olyckor som skett mellan mänskliga förare och automatiserade fordon kan förklaras genom en bristande förståelse för de automatiserade fordonets beteende. Det är därför viktigt att ta reda på hur människor förstår automatiserade fordons förmågor och begränsningar. SAE International, en global yrkeskår får ingenjörer verksamma inom fordonsindustrin, har definierat ett ramverk som beskriver funktionaliteten hos automatiserade fordon i 6 olika nivåer. Den rapporterade studien undersökte med utgångspunkt i detta ramverk vilken automationsgrad deltagarna antar att en självkörande buss har genom deltagarnas upplevelse av fordonet. Inom ramarna för studien färdades deltagarna en kort sträcka på en självkörande buss och besvarade en enkät om hur de ser på bussens förmågor och begränsningar både före och efter färden. Studieresultatet visade att hälften av deltagarna överskattade bussens automationsgrad. Efter att ha färdats med bussen justerade deltagarna ner sina förväntningar på fordonets körförmåga vilket stämde bättre överens med bussens förmågor och begränsningar. Deltagarna rapporterade även att de var mer säkra i sina bedömningar efter erfarenhet av fordonet. Sammanfattningsvis tyder resultatet på att (1) människor tenderar att överskatta automatiserade fordons körförmåga, men att (2) deras uppfattning justeras i samband med att de kommer i kontakt med det automatiserade fordonet i verkligheten och att (3) de då även blir mer säkra i sina bedömningar. Detta borde tas i beaktning vid utveckling av självkörande fordon för att minska risken för olyckor i trafiken.

[730] Erik Lundin. 2022.
Generating Directed & Weighted Synthetic Graphs using Low-Rank Approximations.
Student Thesis. 65 pages. ISRN: LIU-IDA/LITH-EX-A--2022/042--SE.

Generative models for creating realistic synthetic graphs constitute a research area that is increasing in popularity, especially as the use of graph data is becoming increasingly common. Generating realistic synthetic graphs enables sharing of the information embedded in graphs without directly sharing the original graphs themselves. This can in turn contribute to an increase of knowledge within several domains where access to data is normally restricted, including the financial system and social networks. In this study, it is examined how existing generative models can be extended to be compatible with directed and weighted graphs, without limiting the models to generating graphs of a specific domain. Several models are evaluated, and all use low-rank approximations to learn structural properties of directed graphs. Additionally, it is evaluated how node embeddings can be used with a regression model to add realistic edge weights to directed graphs.The results show that the evaluated methods are capable of reproducing global statistics from the original directed graphs to a promising degree, without having more than 52% overlap in terms of edges. The results also indicate that realistic directed and weighted graphs can be generated from directed graphs by predicting edge weights using pairs of node embeddings. However, the results vary depending on which node embedding technique is used.

[729] Evelina Holmgren and Simon Wijk Stranius. 2022.
A Multi-Agent Pickup and Delivery System for Automated Stores with Batched Tasks.
Student Thesis. 101 pages. ISRN: LIU-IDA/LITH-EX-A--22/038--SE.

Throughout today’s society, increasingly more areas are being automated. Grocery stores however have been the same for years. Only recently, self-checkout counters and online shopping have been utilised in this business area. This thesis aims to take it to the next step by introducing automated grocery stores using a multi-agent system. Orders will be given to the system, and on a small area, multiple agents will pick the products in a time-efficient way and deliver them to the customer. This can both increase the throughput but also decrease the food waste and energy consumption of grocery stores. This thesis investigates already existing solutions for the multi-agent pickup and delivery problem. It extends these to the important case of batched tasks in order to improve the customer experience. Batches of tasks represent shopping carts, where fast completion of whole batches gives greater customer satisfaction. This notion is not mentioned in related work, where completion of single tasks is the main goal. Because of this, the existing solution does not accommodate the need of batches or the importance of completing whole batches fast and in somewhat linear order. For this purpose, a new metric called batch ordering weighted error (BOWE) was created that takes these factors into consideration. Using BOWE, one existing algorithm has been extended into prioritizing completing whole batches and is now called B-PIBT. This new algorithm has significantly improved BOWE and even batch service time for the algorithm in key cases and is now superior in comparison to the other state-of-the-art algorithms.

[728] Aksel Holmgren. 2022.
Out of sight, out of mind?: Assessing human attribution of object permanence†capabilities to self-driving cars.
Student Thesis. 34 pages. ISRN: LIU-IDA/KOGVET-G--22/016--SE.

Autonomous vehicles are regularly predicted to be on the verge of broad integration into regular traffic. A crucial aspect of successful traffic interactions is one agent’s ability to adequately understand other agents’ capabilities and limitations. Within the current state of the art concerning self-driving cars, there is a discrepancy between what people tend to believe the capabilities of self-driving cars are, and what those capabilities actually are. The aim of this study was to investigate whether people attribute the capacity of object permanence to self-driving cars roughly in the same manner as they would to a human driver. The study was conducted with online participants (N = 105).The results showed that the participants did not attribute object permanence differently between a self-driven car and a human driver. This indicates that people attribute object permanence similarly to self-driving cars as they do toward human drivers. Furthermore, the results indicate no connection between participants’ tendency to anthropomorphize and whether they attributed object permanence or not. The findings provide evidence for the issues connected to the perceptual belief problem in human-robot interaction, where people attribute capabilities to autonomous vehicles that are not there. The results highlight the importance of understanding which mechanisms underlie these attributions as well as when they happen, in order to mitigate unrealistic expectations.

[727] David ŇngstrŲm. 2022.
Genetic Algorithms for optimizing†behavior trees in air combat.
Student Thesis. 40 pages.

Modelling and simulating entities in virtual environments are tools commonly used by companies to test, validate and verify their products in close to real scenarios; effectivelyreducing the cost, time and effort compared to real life testing. This is especially the case in the area of air combat where realistic behaviors are not only a necessity, but paramount to replace the costs of fuel and operation time. The behavior tree framework is a behavior model whichrepresents entity actions with regards to its perception of the world whilst being easy to manuallyvalidate through its intuitively structured nature. However, as different simulated scenarios require different behaviors, operators commonly has to manually craft new behavior trees at the cost of time and effort.In this thesis, the AI technique Genetic Algorithms (GA) is used to improve a previously crafted general behavior tree with regards to a given 4v4 beyond-visual-range air combat scenario. To this end, a select number of parameters within the behavior tree are optimized in two experiments where a) all parameters are optimized globally and b) the parameters are divided into blocks of sub-behaviors (Engage, Fire missile, etc.) which are then optimized individuallyand combined at a later stage. The agents in the GA are put against the base tree where the baseline is referred to as the base tree vs itself. As the problem proved too easy and resulted in an over-optimized behavior when a single scenario was used, the decision was made to increase the number of the scenarios to three; differing in positions and orientations. The former experimentresulted in a behavior capable of defeating all entities in the other team without any casualties in all three scenarios while the behavior in the latter experiment failed to find the cross-blockrelations, and thus, only achieved a slightly better result than that of the baseline. However, the parameters of highest importance are found to be highly correlated in both experiments and GA is concluded to be a satisfactory technique for the problem of generating improved behaviors with regards to given scenarios.

[726] William Bergekrans. 2022.
Automatic Man Overboard Detection with an RGB Camera: Using convolutional neural networks.
Student Thesis. 50 pages. ISRN: LIU-IDA/LITH-EX-A--22/036--SE.

Man overboard is one of the most common and dangerous accidents that can occur whentraveling on a boat. Available research on man overboard systems with cameras have focusedon man overboard taking place from larger ships, which involves a fall from a height.Recreational boat manufacturers often use cord-based kill switches that turns of the engineif the wearer falls overboard. The aim of this thesis is to create a man overboard warningsystem based on state-of-the-art object detection models that can detect man overboard situationthrough inputs from a camera. Awell performing warning system would allow boatmanufactures to comply with safety regulations and expand the kill-switch coverage to allpassengers on the boat. Furthermore, the aim is also to create two new datasets: one dedicatedto human detection and one with man overboard fall sequences. YOLOv5 achievedthe highest performance on a new human detection dataset, with an average precision of97%. A Mobilenet-SSD-v1 network based on weights from training on the PASCAL VOCdataset and additional training on the new man overboard dataset is used as the detectionmodel in final warning system. The man overboard warning system achieves an accuracyof 50% at best, with a precision of 58% and recall of 78%.

[725] Finn Rietz, Sven Magg, Fredrik Heintz, Todor Stoyanov, Stefan Wermter and Johannes A. Stork. 2022.
Hierarchical goals contextualize local reward decomposition explanations.
Neural Computing & Applications, ??(??):????. Springer London Ltd.
DOI: 10.1007/s00521-022-07280-8.
Publication status: Epub ahead of print
Note: Funding Agencies|Orebro University; Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; Federal Ministry for Economic Affairs and Climate [FKZ 20X1905A-D]
fulltext:print: http://liu.diva-portal.org/smash/get/div...

One-step reinforcement learning explanation methods account for individual actions but fail to consider the agents future behavior, which can make their interpretation ambiguous. We propose to address this limitation by providing hierarchical goals as context for one-step explanations. By considering the current hierarchical goal as a context, one-step explanations can be interpreted with higher certainty, as the agents future behavior is more predictable. We combine reward decomposition with hierarchical reinforcement learning into a novel explainable reinforcement learning framework, which yields more interpretable, goal-contextualized one-step explanations. With a qualitative analysis of one-step reward decomposition explanations, we first show that their interpretability is indeed limited in scenarios with multiple, different optimal policies-a characteristic shared by other one-step explanation methods. Then, we show that our framework retains high interpretability in such cases, as the hierarchical goal can be considered as context for the explanation. To the best of our knowledge, our work is the first to investigate hierarchical goals not as an explanation directly but as additional context for one-step reinforcement learning explanations.

[724] Christoffer SjŲbergsson. 2022.
Comparison of Distance Metrics for Trace Clustering in Process Mining: An Effort to Simplify Analysis of Usage Patterns in PACS.
Student Thesis. 43 pages. ISRN: LIU-IDA/LITH-EX-A--2022/003--SE.

This study intended to validate if clustering could be used to simplify models generated with process mining. The intention was also to see if these clusters could suggest anything about user efficiency. To that end a new metric where devised, average mean duration deviation. This metric aimed to show if a trace was more or less efficient than a comparative trace. Since the intent was to find traces with similar characteristics the clustering was done with characteristic features instead of time efficiency features. The aim was to find a correlation between efficiency after the fact. A correlation with efficiency could not be found.

[723] Erik Sandewall. 2022.
Všrderingar, Liberalism och Islam.
Book. LinkŲping University Electronic Press. 244 pages. ISBN: 9789179293772, 9789179293949.
DOI: 10.3384/9789179293772.
Note: Granskning:Boken är granskad av en extern granskare. 
Fulltext: https://doi.org/10.3384/9789179293772
Diskutera boken: http://www.liberalkommentar.se/sv/intro-...
preview image: http://liu.diva-portal.org/smash/get/div...

Boken beskriver en tolkning av politisk liberalism som här kallas paraliberalism och som betonar värderingarnas betydelse både för individen och för samhället. Värderingar ses som en central del av individens autonomi, alltså hennes förmåga till självständigt tänkande och handlande med hjälp av kunskap och förnuft, och styrt av ansvarskännande värderingar och förhållningssätt. Autonomi innebär alltså frihet under eget ansvar.I begreppet värderingar ingår också människors förhållningssätt i situationer som de möter. Varje människa har sina egna värderingar, men hon förväntas utveckla dem genom deltagande i en värdekultur där värderingar diskuteras, tillämpas och prövas, och där deltagarna kan komma att revidera sina värderingar. Värderingar kan alltså variera efter lokala förhållanden, men paraliberalismen anger två kardinalvärderingar som har övergripande betydelse, nämligen dels omsorgen om individens autonomi, dels också mänsklighetens ansvar för den egna planeten.Den senare kardinalvärderingen kräver att alla stater samarbetar, vilket ur filosofisk synpunkt betyder att synen på nationsbegreppet och nationalismen behöver omprövas. Autonomibegreppet tillämpas därför inte bara på individer utan också på stater vilka förutsätts styras av värderingar på samma sätt som individer gör det. Vidare förutsätts att stater klargör och försvarar sina samhällsgrundande värderingar, och en nation ses som den huvuddel av statens medborgare som omfattar dessa värderingar.I den sista av bokens fem delar används paraliberalismen som utgångspunkt för studiet av de tolkningar av islam som några framstående islamiska lärde har framfört i böcker och artiklar. Eftersom paraliberalismen är tydligt definierad lämpar den sig bra som bas för meningsutbyte med livsåskådningar som tydligt skiljer sig från liberalismen.

[722] Conor F. Hayes, Roxana R?dulescu, Eugenio Bargiacchi, Johan KšllstrŲm, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowť, Gabriel Ramos, Marcello Restelli, Peter Vamplew and Diederik M. Roijers. 2022.
A practical guide to multi-objective reinforcement learning and planning.
Autonomous Agents and Multi-Agent Systems, 36(1):????. Springer.
DOI: 10.1007/s10458-022-09552-y.
Note: Funding: Fonds voor Wetenschappelijk Onderzoek (FWO)FWO [1SA2820N]; Flemish GovernmentEuropean Commission; FWOFWO [iBOF/21/027]; National University of Ireland Galway Hardiman Scholarship; FAPERGSFundacao de Amparo a Ciencia e Tecnologia do Estado do Rio Grande do Sul (FAPERGS) [19/2551-0001277-2]; FAPESPFundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2020/05165-1]; Swedish Governmental Agency for Innovation SystemsVinnova [NFFP7/2017-04885]; Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; LIFT - Dutch Research Council (NWO) [019.011]; 2017 Microsoft Research PhD Scholarship Program; 2020 Microsoft Research EMEA PhD Award
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Real-world sequential decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives. Despite this, the majority of research in reinforcement learning and decision-theoretic planning either assumes only a single objective, or that multiple objectives can be adequately handled via a simple linear combination. Such approaches may oversimplify the underlying problem and hence produce suboptimal results. This paper serves as a guide to the application of multi-objective methods to difficult problems, and is aimed at researchers who are already familiar with single-objective reinforcement learning and planning methods who wish to adopt a multi-objective perspective on their research, as well as practitioners who encounter multi-objective decision problems in practice. It identifies the factors that may influence the nature of the desired solution, and illustrates by example how these influence the design of multi-objective decision-making systems for complex problems.

[721] Dominik Drexler, Jendrik Seipp and Hector Geffner. 2022.
Learning Sketches for Decomposing Planning Problems into Subproblems of Bounded Width.
In Proceedings of the 32nd International Conference on Automated Planning and Scheduling (ICAPS2022).
arXiv: https://arxiv.org/abs/2203.14852

Recently, sketches have been introduced as a general language for representing the subgoal structure of instances drawn from the same domain. Sketches are collections of rules of the form C -> E over a given set of features where C expresses Boolean conditions and E expresses qualitative changes. Each sketch rule defines a subproblem: going from a state that satisfies C to a state that achieves the change expressed by E or a goal state. Sketches can encode simple goal serializations, general policies, or decompositions of bounded width that can be solved greedily, in polynomial time, by the SIW_R variant of the SIW algorithm. Previous work has shown the computational value of sketches over benchmark domains that, while tractable, are challenging for domain-independent planners. In this work, we address the problem of learning sketches automatically given a planning domain, some instances of the target class of problems, and the desired bound on the sketch width. We present a logical formulation of the problem, an implementation using the ASP solver Clingo, and experimental results. The sketch learner and the SIW_R planner yield a domain-independent planner that learns and exploits domain structure in a crisp and explicit form.

[720] Oskar Skoglund. 2022.
Finding co-workers with similar competencies through data clustering.
Student Thesis. 40 pages. ISRN: LIU-IDA/LITH-EX-A--21/081--SE.

In this thesis, data clustering techniques are applied to a competence database from the company Combitech. The goal of the clustering is to connect co-workers with similar competencies and competence areas in order to enable more skill sharing. This is accomplished by implementing and evaluating three clustering algorithms, k-modes, DBSCAN, and ROCK. The clustering algorithms are fine-tuned with the use of three internal validity indices, the Dunn, Silhouette, and Davies-Bouldin score. Finally, a form regarding the clustering of the three algorithms is sent out to the co-workers, which the clustering is based on, in order to obtain external validation by calculating the clustering accuracy. The results from the internal validity indices show that ROCK and DBSCAN create the most separated and dense clusters. The results from the form show that ROCK is the most accurate of the three algorithms, with an accuracy of 94%, followed by k-modes at 58% and DBSCAN at 40% accuracy. However, the visualization of the clusters shows that both ROCK and DBSCAN create one very big cluster, which is not desirable. This was not the case for k-modes, where the clusters are more evenly sized while still being fairly well-separated. In general, the results show that it is possible to use data clustering techniques to connect people with similar competencies and that the predicted clusters agree fairly well with the gold-standard data from the co-workers. However, the results are very dependent on the choice of algorithm and parametric values, and thus have to be chosen carefully.

[719] Edward Curry, Fredrik Heintz, Morten Irgens, Arnold W. M. Smeulders and Stefano Stramigioli. 2022.
Partnership on AI, Data, and Robotics.
Communications of the ACM, 65(4):54–55. ASSOC COMPUTING MACHINERY.
DOI: 10.1145/3513000.

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[718] Alfred Hagberg and Mustaf Abdullahi Musse. 2022.
Instance Segmentation on depth images using Swin Transformer for improved accuracy on indoor images.
Student Thesis. In series: arXiv.org #??. 43 pages. ISRN: LIU-IDA/LITH-EX-A--2022/004--SE.

The Simultaneous Localisation And Mapping (SLAM) problem is an open fundamental problem in autonomous mobile robotics. One of the latest most researched techniques used to enhance the SLAM methods is instance segmentation. In this thesis, we implement an instance segmentation system using Swin Transformer combined with two of the state of the art methods of instance segmentation namely Cascade Mask RCNN and Mask RCNN. Instance segmentation is a technique that simultaneously solves the problem of object detection and semantic segmentation. We show that depth information enhances the average precision (AP) by approximately 7%. We also show that the Swin Transformer backbone model can work well with depth images. Our results also show that Cascade Mask RCNN outperforms Mask RCNN. However, the results are to be considered due to the small size of the NYU-depth v2 dataset. Most of the instance segmentation researches use the COCO dataset which has a hundred times more images than the NYU-depth v2 dataset but it does not have the depth information of the image.

[717] Johan KšllstrŲm, R. Granlund and Fredrik Heintz. 2022.
Design of simulation-based pilot training systems using machine learning agents.
Aeronautical Journal, ??(??):????. Cambridge University Press.
DOI: 10.1017/aer.2022.8.
Publication status: Epub ahead of print
Note: Funding Agencies|Swedish Governmental Agency for Innovation SystemsVinnova [NFFP7/2017-04885]; Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2020/5-230]
fulltext:print: http://liu.diva-portal.org/smash/get/div...

The high operational cost of aircraft, limited availability of air space, and strict safety regulations make training of fighter pilots increasingly challenging. By integrating Live, Virtual, and Constructive simulation resources, efficiency and effectiveness can be improved. In particular, if constructive simulations, which provide synthetic agents operating synthetic vehicles, were used to a higher degree, complex training scenarios could be realised at low cost, the need for support personnel could be reduced, and training availability could be improved. In this work, inspired by the recent improvements of techniques for artificial intelligence, we take a user perspective and investigate how intelligent, learning agents could help build future training systems. Through a domain analysis, a user study, and practical experiments, we identify important agent capabilities and characteristics, and then discuss design approaches and solution concepts for training systems to utilise learning agents for improved training value.

[716] Filip StrŲmbšck, Linda Mannila and Mariam Kamkar. 2022.
Pilot Study of Progvis: A Visualization Tool for Object Graphs and Concurrency via Shared Memory.
In Australasian Computing Education Conference (ACE ?22) February 14?18, 2022, pages 123–132. Association for Computing Machinery (ACM). ISBN: 978-1-4503-9643-1.
DOI: 10.1145/3511861.3511885.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Concurrency and synchronization are two topics that are becomingincreasingly important for computer science students due to thehigh number of cores available in most modern devices. These aretopics that many students struggle with at first, perhaps partiallydue to the inherent nondeterminism and the difficulty to test forabsence of race conditions. Furthermore, previous research indicate that some common mistakes when working with concurrencymight be due students not connecting the concurrency concepts(such as synchronization) to the data that needs to be protected,especially when pointers and references are involved.To address these issues, we propose Progvis, which is a visualization tool aimed specifically at concurrency using the sharedmemory model. It provides a detailed visualization of objects inmemory and their relation to the running threads in order to helpstudents connect concurrency issues with the affected data. Wehave performed an initial, small scale evaluation on whether usingthe tool helps students solve synchronization problems during voluntary problem-solving sessions. The preliminary results indicatethat students who used the tool did indeed perform better.

[715] Anton Hansson and Hugo Cedervall. 2022.
Insurance Fraud Detection using Unsupervised Sequential Anomaly Detection.
Student Thesis. 63 pages. ISRN: LIU-IDA/LITH-EX-A--21/084--SE.

Note: Gjordes digitalt via Zoom. 

Fraud is a common crime within the insurance industry, and insurance companies want to quickly identify fraudulent claimants as they often result in higher premiums for honest customers. Due to the digital transformation where the sheer volume and complexity of available data has grown, manual fraud detection is no longer suitable. This work aims to automate the detection of fraudulent claimants and gain practical insights into fraudulent behavior using unsupervised anomaly detection, which, compared to supervised methods, allows for a more cost-efficient and practical application in the insurance industry. To obtain interpretable results and benefit from the temporal dependencies in human behavior, we propose two variations of LSTM based autoencoders to classify sequences of insurance claims. Autoencoders can provide feature importances that give insight into the models' predictions, which is essential when models are put to practice. This approach relies on the assumption that outliers in the data are fraudulent. The models were trained and evaluated on a dataset we engineered using data from a Swedish insurance company, where the few labeled frauds that existed were solely used for validation and testing. Experimental results show state-of-the-art performance, and further evaluation shows that the combination of autoencoders and LSTMs are efficient but have similar performance to the employed baselines. This thesis provides an entry point for interested practitioners to learn key aspects of anomaly detection within fraud detection by thoroughly discussing the subject at hand and the details of our work.

[714] Marco Kuhlmann, Andreas Maletti and Lena Katharina Schiffer. 2022.
The tree-generative capacity of combinatory categorial grammars.
Journal of computer and system sciences (Print), 124(??):214–233. Academic Press Ltd - Elsevier Science Ltd.
DOI: 10.1016/j.jcss.2021.10.005.
Note: Funding Agencies|Centre for Industrial IT (CENIIT) [15.02]; German Research Foundation (DFG) Research Training Group GRK 1763 Quantitative Logics and AutomataGerman Research Foundation (DFG)
fulltext:print: http://liu.diva-portal.org/smash/get/div...

The generative capacity of combinatory categorial grammars (CCGs) as generators of tree languages is investigated. It is demonstrated that the tree languages generated by CCGs can also be generated by simple monadic context-free tree grammars. However, the important subclass of pure combinatory categorial grammars cannot even generate all regular tree languages. Additionally, the tree languages generated by combinatory categorial grammars with limited rule degrees are characterized: If only application rules are allowed, then these grammars can generate only a proper subset of the regular tree languages, whereas they can generate exactly the regular tree languages once first-degree composition rules are permitted. (C) 2021 The Author(s). Published by Elsevier Inc.

2021
[713] Ali Basirat, Marc Allassonniere-Tang and Aleksandrs Berdicevskis. 2021.
An empirical study on the contribution of formal and semantic features to the grammatical gender of nouns.
Linguistics Vanguard, 7(1):????. WALTER DE GRUYTER GMBH.
DOI: 10.1515/lingvan-2020-0048.
Note: Funding Agencies|IDEXLYON Fellowship Grant [16-IDEX-0005]; University of Lyon Grant NSCO ED 476 [ANR-10-LABX-0081]; French National Research AgencyFrench National Research Agency (ANR) [ANR-11-IDEX-0007]

This study conducts an experimental evaluation of two hypotheses about the contributions of formal and semantic features to the grammatical gender assignment of nouns. One of the hypotheses (Corbett and Fraser 2000) claims that semantic features dominate formal ones. The other hypothesis, formulated within the optimal gender assignment theory (Rice 2006), states that form and semantics contribute equally. Both hypotheses claim that the combination of formal and semantic features yields the most accurate gender identification. In this paper, we operationalize and test these hypotheses by trying to predict grammatical gender using only character-based embeddings (that capture only formal features), only context-based embeddings (that capture only semantic features) and the combination of both. We performed the experiment using data from three languages with different gender systems (French, German and Russian). Formal features are a significantly better predictor of gender than semantic ones, and the difference in prediction accuracy is very large. Overall, formal features are also significantly better than the combination of form and semantics, but the difference is very small and the results for this comparison are not entirely consistent across languages.

[712] Jenny Kunz and Marco Kuhlmann. 2021.
Test Harder Than You Train: Probing with Extrapolation Splits.
In Jasmijn Bastings, Yonatan Belinkov, Emmanuel Dupoux, Mario Giulianelli, Dieuwke Hupkes, Yuval Pinter, Hassan Sajjad, editors, Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, pages 15–25.
DOI: 10.18653/v1/2021.blackboxnlp-1.2.

Previous work on probing word representations for linguistic knowledge has focused on interpolation tasks. In this paper, we instead analyse probes in an extrapolation setting, where the inputs at test time are deliberately chosen to be ‚Äėharder‚Äô than the training examples. We argue that such an analysis can shed further light on the open question whether probes actually decode linguistic knowledge, or merely learn the diagnostic task from shallow features. To quantify the hardness of an example, we consider scoring functions based on linguistic, statistical, and learning-related criteria, all of which are applicable to a broad range of NLP tasks. We discuss the relative merits of these criteria in the context of two syntactic probing tasks, part-of-speech tagging and syntactic dependency labelling. From our theoretical and experimental analysis, we conclude that distance-based and hard statistical criteria show the clearest differences between interpolation and extrapolation settings, while at the same time being transparent, intuitive, and easy to control.

[711] Filip StrŲmbšck, Linda Mannila and Mariam KAMKAR. 2021.
The Non-Deterministic Path to Concurrency ? Exploring how Students Understand the Abstractions of Concurrency.
Informatics in Education. An International Journal, 20(4):683–715. Vilnius University Press.
DOI: 10.15388/infedu.2021.29.
Fulltext: https://doi.org/10.15388/infedu.2021.29
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Concurrency is often perceived as difficult by students. One reason for this may be due to the fact that abstractions used in concurrent programs leave more situations undefined compared to sequential programs (e.g., in what order statements are executed), which makes it harder to create a proper mental model of the execution environment. Students who aim to explore the abstractions through testing are further hindered by the non-determinism of concurrent programs since even incorrect programs may seem to work properly most of the time. In this paper we aim to explore how students understanding these abstractions by examining 137 solutions to two concurrency questions given on the final exam in two years of an introductory concurrency course. To highlight problematic areas of these abstractions, we present alternative abstractions under which each incorrect solution would be correct.

[710] Pontus Haglund, Filip StrŲmbšck and Linda Mannila. 2021.
Understanding Students? Failure to use Functions as a Tool for Abstraction ? An Analysis of Questionnaire Responses and Lab Assignments in a CS1 Python Course.
Informatics in Education. An International Journal, 20(4):583–614. Vilnius University Press.
DOI: 10.15388/infedu.2021.26.
Fulltext: https://doi.org/10.15388/infedu.2021.26
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Controlling complexity through the use of abstractions is a critical part of problem solving in programming. Thus, becoming proficient with procedural and data abstraction through the use of user-defined functions is important. Properly using functions for abstraction involves a number of other core concepts, such as parameter passing, scope and references, which are known to be difficult. Therefore, this paper aims to study students proficiency with these core concepts, and students ability to apply procedural and data abstraction to solve problems. We collected data from two years of an introductory Python course, both from a questionnaire and from two lab assignments. The data shows that students had difficulties with the core concepts, and a number of issues solving problems with abstraction. We also investigate the impact of using a visualization tool when teaching the core concepts.

[709] David GrŲnberg. 2021.
Extracting Salient Named Entities from Financial News Articles.
Student Thesis. ISRN: LIU-IDA/LITH-EX-A--21/040--SE.

This thesis explores approaches for extracting company mentions from financial newsarticles that carry a central role in the news. The thesis introduces the task of salient named entity extraction (SNEE): extract all salient named entity mentions in a text document. Moreover, a neural sequence labeling approach is explored to address the SNEE task in an end-to-end fashion, both using a single-task and a multi-task learning setup. In order to train the models, a new procedure for automatically creating SNEE annotations for an existing news article corpus is explored. The neural sequence labeling approaches are compared against a two-stage approach utilizing NLP parsers, a knowledge base and a salience classifier. Textual features inspired from related work in salient entity detection are evaluated to determine what combination of features results in the highest performance on the SNEE task when used by a salience classifier. The experiments show that the difference in performance between the two-stage approach and the best performing sequence labeling approach is marginal, demonstrating the potential of the end-to-end sequence labeling approach on the SNEE task.

[708] Erik Nikko, Zoran Sjanic and Fredrik Heintz. 2021.
Towards Verification and Validation of Reinforcement Learning in Safety-Critical Systems: A Position Paper from the Aerospace Industry.
In Robust and Reliable Autonomy in the Wild, International Joint Conferences on Artificial Intelligence.
Link to paper: http://rbr.cs.umass.edu/r2aw/papers/R2AW...

Reinforcement learning techniques have successfully been applied to solve challenging problems. Among the more famous examples are playing games such as Go and real-time computer games such as StarCraft II. In addition, reinforcement learning has successfully been deployed in cyber-physical systems such as robots playing a curling-based game. These are all important and significant achievements indicating that the techniques can be of value for the aerospace industry. However, to use these techniques in the aerospace industry, very high requirements on verification and validation must be met. In this position paper, we outline four key problems for verification and validation of reinforcement learning techniques. Solving these are an important step towards enabling reinforcement learning techniques to be used in safety critical domains such as the aerospace industry.

[707] Johan KšllstrŲm, Rego Granlund and Fredrik Heintz. 2021.
Design of Simulation-Based Pilot Training Systems using Machine Learning Agents.
In Proceedings of the 32nd Congress of the International Council of Aeronautical Sciences (ICAS). The International Council of the Aeronautical Sciences. ISBN: 9783932182914.
ICAS 2020/21 - CD-ROM PROCEEDINGS: https://www.icas.org/ICAS_ARCHIVE/ICAS20...

The high operational cost of aircraft, limited availability of air space, and strict safety regulations make training of fighter pilots increasingly challenging. By integrating Live, Virtual, and Constructive simulation resources, efficiency and effectiveness can be improved. In particular, if constructive simulations, which provide synthetic agents operating synthetic vehicles, were used to a higher degree, complex training scenarios could be realized at low cost, the need for support personnel could be reduced, and training availability could be improved. In this work, inspired by the recent improvements of techniques for artificial intelligence, we take a user perspective and investigate how intelligent, learning agents could help build future training systems. Through a domain analysis, a user study, and practical experiments, we identify important agent capabilities and characteristics, and then discuss design approaches and solution concepts for training systems to utilize learning agents for improved training value.

[706] Nguyen Linh Anh and Andrzej Szalas. 2021.
Optimization Models for Medical Procedures Relocation.
In Watrobski J., Salabun W., Toro C., Zanni-Merk C., Howlett R.J, Lakhmi C.J., editors, 25th KES International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES), pages 2058–2067. In series: Procedia Computer Science #192. Elsevier.
DOI: 10.1016/j.procs.2021.08.212.
Note: Funding: Polish Ministry of Science and Higher EducationMinistry of Science and Higher Education, Poland
Fulltext: https://doi.org/10.1016/j.procs.2021.08....

As a side-effect of the Covid-19 pandemic, significant decreases in medical procedures for noncommunicable diseases have been observed. This calls for a decision support assisting in the analysis of opportunities to relocate procedures among hospitals in an efficient or, preferably, optimal manner. In the current paper we formulate corresponding decision problems and develop linear (mixed integer) programming models for them. Since solving mixed integer programming problems is NP-complete, we verify experimentally their usefulness using real-world data about urological procedures. We show that even for large models, with millions of variables, the problems’ instances are solved in perfectly acceptable time.

[705] Andrzej Szalas. 2021.
Many-Valued Dynamic Object-Oriented Inheritance and Approximations.
In Ramanna S., Cornelis C., Ciucci D., editors, International Joint Conference on Rough Sets, pages 103–119. In series: Lecture Notes in Computer Science #12872. Springer. ISBN: 9783030873332, 9783030873349.
DOI: 10.1007/978-3-030-87334-9_10.
Note: Funding: Polish National Science Centre [2017/27/B/ST6/02018]

The majority of contemporary software systems are developed using object-oriented tools and methodologies, where constructs like classes, inheritance and objects are first-class citizens. In the current paper we provide a novel formal framework for many-valued object-oriented inheritance in rule-based query languages. We also relate the framework to rough set-like approximate reasoning. Rough sets and their generalizations have intensively been studied and applied. However, the mainstream of the area mainly focuses on the context of information and decision tables. Therefore, approximations defined in the much richer object-oriented contexts generalize known approaches.

[704] Gerald Steinbauer, Martin Kandlhofer, Tara Chklovski, Fredrik Heintz and Sven Koenig. 2021.
Education in Artificial Intelligence K-12.
KŁnstliche Intelligenz, 35(2):127–129. Springer.
DOI: 10.1007/s13218-021-00734-6.
Note: Funding Agencies: Graz University of Technology
fulltext:print: http://liu.diva-portal.org/smash/get/div...

[703] Jendrik Seipp, Thomas Keller and Malte Helmert. 2021.
Saturated Post-hoc Optimization for Classical Planning.
In Proceedings of the 35th AAAI Conference on Artificial Intelligence, pages 11947–11953. In series: AAAI Conference on Artificial Intelligence #??. Assoc Advancement Artifical Intelligence. ISBN: 9781577358664.
Note: Funding Agencies|European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programmeEuropean Research Council (ERC) [817639]; TAILOR, a project - EU Horizon 2020 research and innovation programme [952215]

Saturated cost partitioning and post-hoc optimization are two powerful cost partitioning algorithms for optimal classical planning. The main idea of saturated cost partitioning is to give each considered heuristic only the fraction of remaining operator costs that it needs to prove its estimates. We show how to apply this idea to post-hoc optimization and obtain a heuristic that dominates the original both in theory and on the IPC benchmarks.

[702] Fredrik Pršntare, Herman Appelgren and Fredrik Heintz. 2021.
Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment.
In THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, pages 11317–11324. In series: AAAI Conference on Artificial Intelligence #??. ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. ISBN: 9781577358664.
Note: Funding Agencies|Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; TAILOR project - EU Horizon 2020 research and innovation programme [952215]; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation [KAW 2019.0350]

Optimal simultaneous coalition structure generation and assignment is computationally hard. The state-of-the-art can only compute solutions to problems with severely limited input sizes, and no effective approximation algorithms that are guaranteed to yield high-quality solutions are expected to exist. Real-world optimization problems, however, are often characterized by large-scale inputs and the need for generating feasible solutions of high quality in limited time. In light of this, and to make it possible to generate better feasible solutions for difficult large-scale problems efficiently, we present and benchmark several different anytime algorithms that use general-purpose heuristics and Monte Carlo techniques to guide search. We evaluate our methods using synthetic problem sets of varying distribution and complexity. Our results show that the presented algorithms are superior to previous methods at quickly generating near-optimal solutions for small-scale problems, and greatly superior for efficiently finding high-quality solutions for large-scale problems. For example, for problems with a thousand agents and values generated with a uniform distribution, our best approach generates solutions 99.5% of the expected optimal within seconds. For these problems, the state-of-the-art solvers fail to find any feasible solutions at all.

[701] Simon StŚhlberg, Guillem FrancŤs and Jendrik Seipp. 2021.
Learning Generalized Unsolvability Heuristics for Classical Planning.
In Zhi-Hua Zhou, editor, 30th International Joint Conference on Artificial Intelligence, pages 4175–4181.

Recent work in classical planning has introduced dedicated techniques for detecting unsolvable states, i.e., states from which no goal state can be reached. We approach the problem from a generalized planning perspective and learn first-order-like formulas that characterize unsolvability for entire planning domains. We show how to cast the problem as a self-supervised classification task. Our training data is automatically generated and labeled by exhaustive exploration of small instances of each domain, and candidate features are automatically computed from the predicates used to define the domain. We investigate three learning algorithms with different properties and compare them to heuristics from the literature. Our empirical results show that our approach often captures important classes of unsolvable states with high classification accuracy. Additionally, the logical form of our heuristics makes them easy to interpret and reason about, and can be used to show that the characterizations learned in some domains capture exactly all unsolvable states of the domain.

[700] Jonas Lundberg, Mattias Arvola and Karljohan Lundin Palmerius. 2021.
Human Autonomy in Future Drone Traffic: Joint Human-AI Control in Temporal Cognitive Work.
Frontiers in Artificial Intelligence, 4(??):????. Frontiers Media S.A..
DOI: 10.3389/frai.2021.704082.
Note: Funding: Swedish Transport Administration
fulltext:print: http://liu.diva-portal.org/smash/get/div...

The roles of human operators are changing due to increased intelligence and autonomy of computer systems. Humans will interact with systems at a more overarching level or only in specific situations. This involves learning new practices and changing habitual ways of thinking and acting, including reconsidering human autonomy in relation to autonomous systems. This paper describes a design case of a future autonomous management system for drone traffic in cities in a key scenario we call The Computer in Brussels. Our approach to designing for human collaboration with autonomous systems builds on scenario-based design and cognitive work analysis facilitated by computer simulations. We use a temporal method, called the Joint Control Framework to describe human and automated work in an abstraction hierarchy labeled Levels of Autonomy in Cognitive Control. We use the Score notation to analyze patterns of temporal developments that span levels of the abstraction hierarchy and discuss implications for human-automation communication in traffic management. We discuss how autonomy at a lower level can prevent autonomy on higher levels, and vice versa. We also discuss the temporal nature of autonomy in minute-to-minute operative work. Our conclusion is that human autonomy in relation to autonomous systems is based on fundamental trade-offs between technological opportunities to automate and values of what human actors find meaningful.

[699] Florian Pommerening, Thomas Keller, Valentina Halasi, Jendrik Seipp, Silvan Sievers and Malte Helmert. 2021.
Dantzig-Wolfe Decomposition for Cost Partitioning.
In 31st International Conference on Automated Planning and Scheduling . AAAI Press.
Link: https://ojs.aaai.org/index.php/ICAPS/art...

Optimal cost partitioning can produce high quality heuristic estimates even from small abstractions. It can be computed with a linear program (LP) but the size of this LP often makes this impractical. Recent work used Lagrangian decomposition to speed up the computation. Here we use a different decomposition technique called Dantzig-Wolfe decomposition to tackle the problem. This gives new insights into optimal cost partitioning and has several advantages over Lagrangian decomposition: our method detects when a cost partition is optimal; it can deal with general cost functions; and it does not consider abstractions in the linear program that do not contribute to the heuristic value. We also show the advantage of the method empirically and investigate several improvements that are useful for all cost partitioning methods.

[698] Ńlvaro Torralba, Jendrik Seipp and Silvan Sievers. 2021.
Automatic Instance Generation for Classical Planning.
In 31st International Conference on Automated Planning and Scheduling. AAAI Press.
Link: https://ojs.aaai.org/index.php/ICAPS/art...

The benchmarks from previous International Planning Competitions (IPCs) are the de-facto standard for evaluating planning algorithms. The IPC set is both a collection of planning domains and a selection of instances from these domains. Most of the domains come with a parameterized generator that generates new instances for a given set of parameter values. Due to the steady progress of planning research some of the instances that were generated for past IPCs are inadequate for evaluating current planners. To alleviate this problem, we introduce Autoscale, an automatic tool that selects instances for a given domain. Autoscale takes into account constraints from the domain designer as well as the performance of current planners to generate an instance set of appropriate difficulty, while avoiding too much bias with respect to the considered planners. We show that the resulting benchmark set is superior to the IPC set and has the potential of improving empirical evaluation of planning research.

[697] Erik Sandewall. 2021.
Ethics, Human Rights, the Intelligent Robot, and its Subsystem for Moral Beliefs.
International Journal of Social Robotics, 13(4):557–567. Springer.
DOI: 10.1007/s12369-019-00540-z.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

The Universal Declaration of Human Rights specifies a number of properties that characterize human beings, such as dignity, conscience, and several others. In this article we focus on these properties and on how they have been defined in the history of philosophy. We show how they can be interpreted in terms of a prototypical architecture for an intelligent robot, and how the robot can be provided with several aspects of ethical capability in this way. The key idea is to provide the robot with a Moral Belief System that cooperates with, and moderates the robots capability of planning and action.

[696] Axel Wickman. 2021.
Exploring feasibility of reinforcement learning flight route planning.
Student Thesis. 36 pages. ISRN: LIU-IDA/KOGVET-G‚Äď21/031‚ÄĒSE.

Alternativ nerladdning: https://public.axelwickman.com/published...

This thesis explores and compares traditional and reinforcement learning (RL) methods of performing 2D flight path planning in 3D space. A wide overview of natural, classic, and learning approaches to planning s done in conjunction with a review of some general recurring problems and tradeoffs that appear within planning. This general background then serves as a basis for motivating different possible solutions for this specific problem. These solutions are implemented, together with a testbed inform of a parallelizable simulation environment. This environment makes use of random world generation and physics combined with an aerodynamical model. An A* planner, a local RL planner, and a global RL planner are developed and compared against each other in terms of performance, speed, and general behavior. An autopilot model is also trained and used both to measure flight feasibility and to constrain the planners to followable paths. All planners were partially successful, with the global planner exhibiting the highest overall performance. The RL planners were also found to be more reliable in terms of both speed and followability because of their ability to leave difficult decisions to the autopilot. From this it is concluded that machine learning in general, and reinforcement learning in particular, is a promising future avenue for solving the problem of flight route planning in dangerous environments.

[695] Dominik Drexler, Jendrik Seipp and Hector Geffner. 2021.
Expressing and Exploiting the Common Subgoal Structure of Classical Planning Domains Using Sketches.
In 18th International Conference on Principles of Knowledge Representation and Reasoning, Hanoi, November 3-12, 2021.

Width-based planning methods deal with conjunctive goals by decomposing problems into subproblems of low width. Algorithms like SIW thus fail when the goal is not easily serializable in this way or when some of the subproblems have a high width. In this work, we address these limitations by using a simple but powerful language for expressing finer problem decompositions introduced recently by Bonet and Geffner, called policy sketches. A policy sketch R over a set of Boolean and numerical features is a set of sketch rules that express how the values of these features are supposed to change. Like general policies, policy sketches are domain general, but unlike policies, the changes captured by sketch rules do not need to be achieved in a single step. We show that many planning domains that cannot be solved by SIW are provably solvable in low polynomial time with the SIW_R algorithm, the version of SIW that employs user-provided policy sketches. Policy sketches are thus shown to be a powerful language for expressing domain-specific knowledge in a simple and compact way and a convenient alternative to languages such as HTNs or temporal logics. Furthermore, they make it easy to express general problem decompositions and prove key properties of them like their width and complexity.

[694] Fredrik Heintz. 2021.
Three Interviews About K-12 AI Education in America, Europe, and Singapore.
KŁnstliche Intelligenz, ??(??):????. SPRINGER HEIDELBERG.
DOI: 10.1007/s13218-021-00730-w.
Publication status: Epub ahead of print

As the impact and importance of artificial intelligence (AI) grows, there is a growing trend to teach AI in primary and secondary education (K-12). To provide an international perspective, we have conducted three interviews with practitioners and policy makers from AI4K12 in the US (D. Touretzky, C. Gardner-McCune, and D. Seehorn), from Singapore (L. Liew) and from the European Commission (F. Benini).

[693] Adam Lager. 2021.
Improving Solr search with Natural Language Processing: An NLP implementation for information retrieval in Solr.
Student Thesis. 24 pages. ISRN: LIU-IDA/LITH-EX-G‚Äď21/030‚ÄĒSE.

The field of AI is emerging fast and institutions and companies are pushing the limits of impossibility. Natural Language Processing is a branch of AI where the goal is to understand human speech and/or text. This technology is used to improve an inverted index,the full text search engine Solr. Solr is open source and has integrated OpenNLP makingit a suitable choice for these kinds of operations. NLP-enabled Solr showed great results compared to the Solr that’s currently running on the systems, where NLP-Solr was slightly worse in terms of precision, it excelled at recall and returning the correct documents.

[692] Oskar Hidťn and David BjŲrelind. 2021.
Clustering and Summarization of Chat Dialogues: To understand a company?s customer base.
Student Thesis. 61 pages. ISRN: LIU-IDA/LITH-EX-A--21/037--SE.

The Customer Success department at Visma handles about 200 000 customer chats each year, the chat dialogues are stored and contain both questions and answers. In order to get an idea of what customers ask about, the Customer Success department has to read a random sample of the chat dialogues manually. This thesis develops and investigates an analysis tool for the chat data, using the approach of clustering and summarization. The approach aims to decrease the time spent and increase the quality of the analysis. Models for clustering (K-means, DBSCAN and HDBSCAN) and extractive summarization (K-means, LSA and TextRank) are compared. Each algorithm is combined with three different text representations (TFIDF, S-BERT and FastText) to create models for evaluation. These models are evaluated against a test set, created for the purpose of this thesis. Silhouette Index and Adjusted Rand Index are used to evaluate the clustering models. ROUGE measure together with a qualitative evaluation are used to evaluate the extractive summarization models. In addition to this, the best clustering model is further evaluated to understand how different data sizes impact performance. TFIDF Unigram together with HDBSCAN or K-means obtained the best results for clustering, whereas FastText together with TextRank obtained the best results for extractive summarization. This thesis applies known models on a textual domain of customer chat dialogues, something that, to our knowledge, has previously not been done in literature.

[691] Agaton SjŲberg. 2021.
Extracting Transaction Information from Financial Press Releases.
Student Thesis. 38 pages. ISRN: LIU-IDA/LITH-EX-A--21/039--SE.

DOI: 21/039.

The use cases of Information Extraction (IE) are more or less endless, often consisting of a combination of Named Entity Recognition (NER) and Relation Extraction (RE). One use case of IE is the extraction of transaction information from Norwegian insider transaction Press Releases (PRs), where a transaction consists of at most four entities: the name of the owner performing the transaction, the number of shares transferred, the transaction date, and the price of the shares bought or sold. The relationships between the entities define which entity belongs to which transaction, and whether shares were bought or sold. This report has investigated how a pair of supervised NER and RE models extract this information. Since these Norwegian PRs were not labeled, two different approaches to annotating the transaction entities and their associated relations were investigated, and it was found that it is better to annotate only entities that occur in a relation than annotating all occurrences. Furthermore, the number of PRs needed to achieve a satisfactory result in the IE pipeline was investigated. The study shows that training with about 400 PRs is sufficient for the results to converge, at around 0.85 in F1-score. Finally, the report shows that there is not much difference between a complex RE model and a simple rule-based approach, when applied on the studied corpus.

[690] Felix Nodelijk and Arun Uppugunduri. 2021.
Estimating lighting from unconstrained RGB images using Deep Learning in real-time for superimposed objects in an augmented reality application.
Student Thesis. 62 pages. ISRN: LIU-IDA/LITH-EX-A--21/042‚ÄĒSE.

Modern deep learning enables many new possibilities for automation. Within augmented reality, deep learning can be used to infer the lighting to accurately render superimposed objects with correct lighting to mix seamlessly with the environment. This study aims to find a method of light estimation from RGB images by investigating Spherical Harmonic coefficients and how said coefficients could be inferred for use in an AR application in real-time. The pre-existing method employed by the application estimates the light by comparing two points cheek-to-cheek on a face. This fails to accurately represent the lighting in many situations, causing users to stop using the application. This study investigates a deep learning model that shows significant improvements in regards to the lighting estimation while also achieving fast inference time. The model results were presented to respondents in a survey and was found to be the better method of the two in terms of light estimation. The final model achieved 19 ms in inference time and 0.10 in RMS error.

[689] Daniel Roos. 2021.
Evaluation of BERT-like models for small scale ad-hoc information retrieval.
Student Thesis. 34 pages. ISRN: LIU-IDA/LITH-EX-A--21/051‚ÄĒSE.

Measuring semantic similarity between two sentences is an ongoing research field with big leaps being taken every year. This thesis looks at using modern methods of semantic similarity measurement for an ad-hoc information retrieval (IR) system. The main challenge tackled was answering the question \"What happens when you don’t have situation-specific data?\". Using encoder-based transformer architectures pioneered by Devlin et al., which excel at fine-tuning to situationally specific domains, this thesis shows just how well the presented methodology can work and makes recommendations for future attempts at similar domain-specific tasks. It also shows an example of how a web application can be created to make use of these fast-learning architectures.

[688] Philip Palapelas Kantola. 2021.
Extreme Quantile Estimation of Downlink Radio Channel Quality.
Student Thesis. 46 pages. ISRN: LIU-IDA/LITH-EX-A--21/048--SE.

The application area of Fifth Generation New Radio (5G-NR) called Ultra-Reliable and Low-Latency Communication (URLLC) requires a reliability, the probability of receiving and decoding a data packet correctly, of 1 - 10^5. For this requirement to be fulfilled in a resource-efficient manner, it is necessary to have a good estimation of extremely low quan- tiles of the channel quality distribution, so that appropriate resources can be distributed to users of the network system. This study proposes and evaluates two methods for estimating extreme quantiles of the downlink channel quality distribution, linear quantile regression and Quantile Regression Neural Network (QRNN). The models were trained on data from Ericsson’s system-level radio network simulator, and evaluated on goodness of fit and resourcefulness. The focus of this study was to estimate the quantiles 10^2, 10^3 and 10^4 of the distribution. The results show that QRNN generally performs better than linear quantile regression in terms of pseudoR2, which indicates goodness of fit, when the sample size is larger. How- ever, linear quantile regression was more effective for smaller sample sizes. Both models showed difficulty estimating the most extreme quantiles. The less extreme quantile to esti- mate, the better was the resulting pseudoR2-score. For the largest sample size, the resulting pseudoR2-scores of the QRNN was 0.20, 0.12 and 0.07, and the scores of linear quantile regression was 0.16, 0.10 and 0.07 for the respective quantiles 10^2, 10^3 and 10^4. It was shown that both evaluated models were significantly more resourceful than us- ing the average of the 50 last measures of channel quality subtracted with a fixed back-off value as a predictor. QRNN had the most optimistic predictions. If using the QRNN, theo- retically, on average 43% more data could be transmitted while fulfilling the same reliability requirement than by using the fixed back-off value.

[687] Axel Holmberg and Wilhelm Hansson. 2021.
Kombinatorisk Optimering med Pointer Networks och Reinforcement Learning.
Student Thesis. ISRN: LIU-IDA/LITH-EX-A--21/035‚ÄĒSE.

Given the complexity and range of combinatorial optimization problems, solving them can be computationally easy or hard. There are many ways to solve them, but all available methods share a problem: they take a long time to run and have to be rerun when new cases are introduced. Machine learning could prove a viable solution to solving combinatorial optimization problems due to the possibility for models to learn and generalize, eliminating the need to run a complex algorithm every time a new instance is presented. Uniter is a management consulting firm that provides services within product modularization. Product modularization results in the possibility for many different product variations to be created based on customer needs. Finding the best combination given a specific customer's need will require solving a combinatorial optimization problem. Based on Uniter's need, this thesis sought to develop and evaluate a machine learning model consisting of a Pointer Network architecture and trained using Reinforcement Learning. The task was to find the combination of parts yielding the lowest cost, given a use case. Each use case had different attributes that specified the need for the final product. For each use case, the model was tasked with selecting the most appropriate combination from a set of 4000 distinct combinations. Three experiments were conducted: examining if the model could suggest an optimal solution after being trained on one use case, if the model could suggest an optimal solution of a previously seen use case, and if the model could suggest an optimal solution of an unseen use case. For all experiments, a single data set was used. The suggested model was compared to three baselines: a weighted random selection, a naive model implementing a feed-forward network, and an exhaustive search.The results showed that the proposed model could not suggest an optimal solution in any of the experiments. In most tests conducted, the proposed model was significantly slower at suggesting a solution than any baseline. The proposed model had high accuracy in all experiments, meaning it suggested almost only feasible solutions in the allowed solution space. However, when the model converged, it suggested only one combination for every use case, with the feed-forward baseline showing the same behavior. This behavior could suggest that the model misinterpreted the task and identified a solution that would work in most cases instead of suggesting the optimal solution for each use case. The discussion concludes that an exhaustive search is preferable for the studied data set and that an alternate approach using supervised learning may be a better solution.

[686] David Nyberg. 2021.
Exploring the Capabilities of Generative Adversarial Networks in Remote Sensing Applications.
Student Thesis. ISRN: LIU-IDA/LITH-EX-A--2021/043--SE.

attachment: http://liu.diva-portal.org/smash/get/div...

The field of remote sensing uses imagery captured from satellites, aircrafts, and UAVs in order to observe and analyze the Earth. Many remote sensing applications that are used today employ deep learning models that require large amounts of data or specific types of data. The lack of data can hinder model performance. A generative adversarial network (GAN) is a deep learning model that can generate synthetic data and can be used as a method for data augmentation to increase performance of data reliant deep learning models. GANs are also capable of image-to-image translation such as transforming a satellite image containing cloud coverage into one without clouds. These possibilities have led to many new and exciting GAN applications.This thesis explores ways generative adversarial networks (GANs) can be applied in a variety of remote sensing applications. To evaluate this, four experiments using GANs are implemented. The tasks are: generating synthetic aerial forestry imagery, translating a satellite segmentation mask into a real satellite image, removal of thin cloud cover from a satellite image, and super resolution to increase the resolution of a satellite image. In all experiments the tasks were deemed successful and prove the potential for further use of GANs in the field of remote sensing.

[685] Lukas Borggren. 2021.
Automatic Categorization of News Articles With Contextualized Language Models.
Student Thesis. 63 pages. ISRN: LIU-IDA/LITH-EX-A--21/038--SE.

This thesis investigates how pre-trained contextualized language models can be adapted for multi-label text classification of Swedish news articles. Various classifiers are built on pre-trained BERT and ELECTRA models, exploring global and local classifier approaches. Furthermore, the effects of domain specialization, using additional metadata features and model compression are investigated. Several hundred thousand news articles are gathered to create unlabeled and labeled datasets for pre-training and fine-tuning, respectively. The findings show that a local classifier approach is superior to a global classifier approach and that BERT outperforms ELECTRA significantly. Notably, a baseline classifier built on SVMs yields competitive performance. The effect of further in-domain pre-training varies; ELECTRA’s performance improves while BERT’s is largely unaffected. It is found that utilizing metadata features in combination with text representations improves performance. Both BERT and ELECTRA exhibit robustness to quantization and pruning, allowing model sizes to be cut in half without any performance loss.

[684] Andreas Magnvall and Alexander Henne. 2021.
Real-time Aerial Photograph Alignment using Feature Matching.
Student Thesis. 21 pages. ISRN: LIU-IDA/LITH-EX-G--21/035--SE.

With increased mobile hardware capabilities, improved UAVs and modern algorithms, accurate maps can be created in real-time by capturing overlapping photographs of the ground. A method for mapping that can be used is to position photos by relying purely on the GPS position and altitude. However, GPS inaccuracies will be visible in the created map. In this paper, we will instead present a method for aligning the photos correctly with the help of feature matching. Feature matching is a well-known method which analyses two photos to find similar parts. If an overlap exists, feature matching can be used to find and localise those parts, which can be used for positioning one image over the other at the overlap. When repeating the process, a whole map can be created. For this purpose, we have also evaluated a selection of feature detection and matching algorithms. The algorithm found to be the best was SIFT with FLANN, which was then used in a prototype for creating a complete map of a forest. Feature matching is in many cases superior to GPS positioning, although it cannot be fully depended on as failed or incorrect matching is a common occurrence.

[683] Agnes Hallberg. 2021.
Using Low-Code Platforms to Collect Patient-Generated Health Data: A Software Developer?s Perspective.
Student Thesis. ISRN: LIU-IDA/LITH-EX-G--21/034--SE.

The act of people collecting their health data through health apps on their smartphones is becoming increasingly popular. Still, it is difficult for healthcare providers to use this patient-generated health data since health apps cannot easily share its data with the health care providers’ Electronic Health Records (EHR). Simultaneously, it is becoming increasingly popular to use low-code platforms for software development. This thesis explored using low-code platforms to create applications intended to collect patient-generated health data and send it to EHRs by creating a web application prototype with the low-code platforms Mendix and Better EHR Studio. During the web application prototype development, the developer conducted a diary to capture their impressions of Mendix to show how a developer experiences developing in a low-code platform compared to traditional programming. The result shows that it is impractical to create applications intended to collect patient-generated health data with the two low-code platforms chosen. The analysis of the conducted diary showed that using a low-code platform is straightforward but also challenging for an experienced software developer.

[682] Anna Lindqvist. 2021.
Threats to smart buildings: Securing devices in a SCADA network.
Student Thesis. ISRN: LIU-IDA/LITH-EX-G--21/038--SE.

This paper examines the possibilities of performing tests with the aim to ensure that devices in a SCADA network can be deemed secure before deployment. SCADA systems are found in most industries and have recently seen an increased use in building automation, most importantly the healthcare sector, which means that a successful attack toward such a system could endanger lives of patients and healthcare professionals.The method of testing was created to examine whether devices conflicted with the security flaws identified by OWASP IoT Top 10 list, meaning that OWASP IoT Top 10 was the foundation for the methodology used in this paper.Results of the tests show that the devices used in testing are not in conflict with the OWASP IoT Top 10 list when using the default settings. However, some settings that can be enabled on the devices would constitute a security risk if enabled.

[681] Patrick Lundberg. 2021.
Verktyg fŲr hyperparameteroptimering.
Student Thesis. 8 pages. ISRN: LIU-IDA/LITH-EX-G--21/042--SE.

Hyperparameteroptimering är ett viktigt uppdrag för att effektivt kunna använda en modell för maskininlärning. Att utföra detta manuellt kan vara tidskrävande, utan garanti för god kvalitet på resulterande hyperparametrar. Att använda verktyg för detta ändamål är att föredra, men det finns ett stort antal verktyg som använder olika algoritmer. Hur effektiva dessa olika verktyg är relativt varandra är ett mindre utforskat område. Denna studie bidrar med en enkel analys av hur två verktyg för sökning av hyperparametrar, Scikit och Ray Tune, fungerar i jämförelse med varandra.

[680] Gerald Steinbauer, Martin Kandlhofer, Tara Chklovski, Fredrik Heintz and Sven Koenig. 2021.
A Differentiated Discussion About AI Education K-12.
KŁnstliche Intelligenz, 35(2):131–137. Springer Nature.
DOI: 10.1007/s13218-021-00724-8.
Note: Funding Agencies|Graz University of Technology
fulltext:print: http://liu.diva-portal.org/smash/get/div...

AI Education for K-12 and in particular AI literacy gained huge interest recently due to the significantly influence in daily life, society, and economy. In this paper we discuss this topic of early AI education along four dimensions: (1) formal versus informal education, (2) cooperation of researchers in AI and education, (3) the level of education, and (4) concepts and tools.

[679] Johan Lind. 2021.
Evaluating CNN-based models for unsupervised image denoising.
Student Thesis. 43 pages. ISRN: LIU-IDA/LITH-EX-A--21/011--SE.

Images are often corrupted by noise which reduces their visual quality and interferes with analysis. Convolutional Neural Networks (CNNs) have become a popular method for denoising images, but their training typically relies on access to thousands of pairs of noisy and clean versions of the same underlying picture. Unsupervised methods lack this requirement and can instead be trained purely using noisy images.This thesis evaluated two different unsupervised denoising algorithms: Noise2Self (N2S) and Parametric Probabilistic Noise2Void (PPN2V), both of which train an internal CNN to denoise images. Four different CNNs were tested in order to investigate how the performance of these algorithms would be affected by different network architectures. The testing used two different datasets: one containing clean images corrupted by synthetic noise, and one containing images damaged by real noise originating from the camera used to capture them.Two of the networks, UNet and a CBAM-augmented UNet resulted in high performance competitive with the strong classical denoisers BM3D and NLM. The other two networks - GRDN and MultiResUNet - on the other hand generally caused poor performance.

[678] Fredrik Pršntare, Herman Appelgren and Fredrik Heintz. 2021.
Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment.
In .

Optimal simultaneous coalition structure generation and assignment is computationally hard. The state-of-the-art can only compute solutions to problems with severely limited input sizes, and no effective approximation algorithms that are guaranteed to yield high-quality solutions are expected to exist. Real-world optimization problems, however, are often characterized by large-scale inputs and the need for generating feasible solutions of high quality in limited time. In light of this, and to make it possible to generate better feasible solutions for difficult large-scale problems efficiently, we present and benchmark several different anytime algorithms that use general-purpose heuristics and Monte Carlo techniques to guide search. We evaluate our methods using synthetic problem sets of varying distribution and complexity. Our results show that the presented algorithms are superior to previous methods at quickly generating near-optimal solutions for small-scale problems, and greatly superior for efficiently finding high-quality solutions for large-scale problems. For example, for problems with a thousand agents and values generated with a uniform distribution, our best approach generates solutions 99.5% of the expected optimal within seconds. For these problems, the state-of-the-art solvers fail to find any feasible solutions at all.

[677] Oskar HolmstrŲm. 2021.
Exploring Transformer-Based Contextual Knowledge Graph Embeddings: How the Design of the Attention Mask and the Input Structure Affect Learning in Transformer Models.
Student Thesis. 41 pages. ISRN: LIU-IDA/LITH-EX-A--21/002--SE.

The availability and use of knowledge graphs have become commonplace as a compact storage of information and for lookup of facts. However, the discrete representation makes the knowledge graph unavailable for tasks that need a continuous representation, such as predicting relationships between entities, where the most probable relationship needs to be found. The need for a continuous representation has spurred the development of knowledge graph embeddings. The idea is to position the entities of the graph relative to each other in a continuous low-dimensional vector space, so that their relationships are preserved, and ideally leading to clusters of entities with similar characteristics. Several methods to produce knowledge graph embeddings have been created, from simple models that minimize the distance between related entities to complex neural models. Almost all of these embedding methods attempt to create an accurate static representation of each entity and relation. However, as with words in natural language, both entities and relations in a knowledge graph hold different meanings in different local contexts. With the recent development of Transformer models, and their success in creating contextual representations of natural language, work has been done to apply them to graphs. Initial results show great promise, but there are significant differences in archi- tecture design across papers. There is no clear direction on how Transformer models can be best applied to create contextual knowledge graph embeddings. Two of the main differences in previous work is how the attention mask is applied in the model and what input graph structures the model is trained on. This report explores how different attention masking methods and graph inputs affect a Transformer model (in this report, BERT) on a link prediction task for triples. Models are trained with five different attention masking methods, which to varying degrees restrict attention, and on three different input graph structures (triples, paths, and interconnected triples). The results indicate that a Transformer model trained with a masked language model objective has the strongest performance on the link prediction task when there are no restrictions on how attention is directed, and when it is trained on graph structures that are sequential. This is similar to how models like BERT learn sentence structure after being exposed to a large number of training samples. For more complex graph structures it is beneficial to encode information of the graph structure through how the attention mask is applied. There also seems to be some indications that the input graph structure affects the models’ capabilities to learn underlying characteristics in the knowledge graph that is trained upon.

[676] Rasmus Larsson. 2021.
Creating Digital Twin Distributed Networks Using Switches With Programmable Data Plane.
Student Thesis. 70 pages. ISRN: LIU-IDA/LITH-EX-A--2021/009--SE.

The domain specific language P4 is a novel initiative which extends the Software-Defined Networking (SDN) paradigm by allowing for data plane programmability. Network virtualisation is a class of network technologies which can be used to abstract the addressing in a network, allowing multiple tenants to utilise the network resources while being agnostic to the underlying network and the other tenants. In other words, <em>twins</em> of tenants using the same addresses can co-exist on the same underlying network. If a twin is a distributed network, it may even be spread out across multiple sites which are connected to a common backbone.In this study, network virtualisation using P4 is evaluated with emphasis on scalability in terms of number of twins and sites. A set of potential network virtualisation technologies are identified and categorised. Based on this categorisation, two variations of network virtualisation are implemented on the P4 capable software switch BMv2 and the performance of both variations are evaluated against the non-P4 solution Linux bridge. Linux bridge was found to yield 451 times more useful bandwidth than the best performing P4 implementation on BMv2, while also learning MAC addresses faster and generating less traffic on the backbone. It is concluded that the performance of network virtualisation implemented and running on BMv2 is worse compared to the non-P4 solution Linux bridge.

[675] Carl Brage. 2021.
Synchronizing 3D data between software: Driving 3D collaboration forward using direct links.
Student Thesis. 43 pages. ISRN: LIU-IDA/LITH-EX-A--21/010‚ÄĒSE.

In the area of 3D visualization there are often several stages in the design process. These stages can involve creating a model, applying a texture to the model and creating a rendered image from the model. Some software can handle all stages of the process while some are focused on a single stage to try to perfect and narrow down the service provided. In this case there needs to be a way to transfer 3D data between software in an efficient way where the user experience isn’t lacking. This thesis explores the area of 3D data synchronization by first getting foundation from the prestudy and literature study. The findings from these studies are used in a shared file-based implementation and a design of a network-based system. The work presented in this thesis forms a comprehensive overview which can be used for future work.

[674] Jendrik Seipp. 2021.
Online Saturated Cost Partitioning for Classical Planning.
In Proceedings of the 31st International Conference on Automated Planning and Scheduling (ICAPS 2021), pages 317–321. AAAI Press. ISBN: 978-1-57735-867-1.
L√§nk till konferensen / Link to proceedings: https://ojs.aaai.org/index.php/ICAPS/iss...

Cost partitioning is a general method for admissibly summing up heuristic estimates for optimal state-space search. Most cost partitioning algorithms can optimize the resulting cost-partitioned heuristic for a specific state. Since computing a new cost-partitioned heuristic for each evaluated state is usually too expensive in practice, the strongest planners based on cost partitioning over abstraction heuristics precompute a set of cost-partitioned heuristics before the search and maximize over their estimates during the search. This makes state evaluations very fast, but since there is no better termination criterion than a time limit, it requires a long precomputation phase, even for the simplest planning tasks. A prototypical example for this is the Scorpion planner which computes saturated cost partitionings over abstraction heuristics offline before the search. Using Scorpion as a case study, we show that by incrementally extending the set of cost-partitioned heuristics online during the search, we drastically speed up the planning process and even often solve more tasks.

[673] Full text  Mattias Tiger, David BergstrŲm, Andreas Norrstig and Fredrik Heintz. 2021.
Enhancing Lattice-Based Motion Planning With Introspective Learning and Reasoning.
IEEE Robotics and Automation Letters, 6(3):4385–4392. Institute of Electrical and Electronics Engineers (IEEE).
DOI: 10.1109/LRA.2021.3068550.
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; National Graduate School in Computer Science (CUGS), Sweden; Excellence Center at Linkoping-Lund for Information Technology (ELLIIT); TAILOR Project - EU Horizon 2020 research and innovation programme [952215]; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation [KAW 2019.0350]
Fulltext: https://doi.org/10.1109/LRA.2021.3068550
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Lattice-based motion planning is a hybrid planning method where a plan is made up of discrete actions, while simultaneously also being a physically feasible trajectory. The planning takes both discrete and continuous aspects into account, for example action pre-conditions and collision-free action-duration in the configuration space. Safe motion planning rely on well-calibrated safety-margins for collision checking. The trajectory tracking controller must further be able to reliably execute the motions within this safety margin for the execution to be safe. In this work we are concerned with introspective learning and reasoning about controller performance over time. Normal controller execution of the different actions is learned using machine learning techniques with explicit uncertainty quantification, for safe usage in safety-critical applications. By increasing the model accuracy the safety margins can be reduced while maintaining the same safety as before. Reasoning takes place to both verify that the learned models stays safe and to improve collision checking effectiveness in the motion planner using more accurate execution predictions with a smaller safety margin. The presented approach allows for explicit awareness of controller performance under normal circumstances, and detection of incorrect performance in abnormal circumstances. Evaluation is made on the nonlinear dynamics of a quadcopter in 3D using simulation.

[672] Dominik Drexler, Jendrik Seipp and David Speck. 2021.
Subset-Saturated Transition Cost Partitioning.
In 31st International Conference on Automated Planning and Scheduling, Guangzhou, August 2-13, 2021, pages 131–139. AAAI Press.
Konferensens fulltext / Conference proceedings: https://ojs.aaai.org/index.php/ICAPS/iss...

Cost partitioning admissibly combines the information from multiple heuristics for optimal state-space search. One of the strongest cost partitioning algorithms is saturated cost partitioning. It considers the heuristics in sequence and assigns to each heuristic the minimal fraction of the remaining costs that are needed for preserving all heuristic estimates. Saturated cost partitioning has recently been generalized in two directions: first, by allowing to use different costs for the transitions induced by the same operator, and second, by preserving the heuristic estimates for only a subset of states. In this work, we unify these two generalizations and show that the resulting subset-saturated transition cost partitioning algorithm usually yields stronger heuristics than the two generalizations by themselves.

[671] Full text  Susanne Kjallander, Linda Mannila, Anna Akerfeldt and Fredrik Heintz. 2021.
Elementary Students First Approach to Computational Thinking and Programming.
Education Sciences, 11(2):????. MDPI.
DOI: 10.3390/educsci11020080.
Note: Funding Agencies|Marcus and Amalia Wallenberg Foundation [MAW 2017.0096]
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Digital competence and programming are actively highlighted areas in education worldwide. They are becoming part of curricula all over the world, including the Swedish elementary school curriculum, Children are expected to develop computational thinking through programming activities, mainly in mathematics-which are supposed to be based on both proven experience and scientific grounds. Both are lacking in the lower grades of elementary school. This article gives unique insight into pupils learning during the first programming lessons based on a group of Swedish pupils experiences when entering school. The goal of the article is to inform education policy and practice. The large interdisciplinary, longitudinal research project studies approximately 1500 students aged 6-16 and their teachers over three years, using video documentation, questionnaires, and focus group interviews. This article reports on empirical data collected during the first year in one class with 30 pupils aged 6-7 years. The social semiotic, multimodal theoretical framework \"Design for Learning\" is used to investigate potential signs of learning in pupils multimodal representations when they, for example, use block programming in the primary and secondary transformation unit. We show that young pupils have positive attitudes to programming and high self-efficacy, and that pupils signs of learning in programming are multimodal and often visible in social interactions.

[670] Full text  Fredrik Pršntare and Fredrik Heintz. 2021.
Hybrid Dynamic Programming for Simultaneous Coalition Structure Generation and Assignment.
In Uchiya, Takahiro, Bai, Quan, Marsa-Maestre, Ivan, editors, PRIMA 2020: Principles and Practice of Multi-Agent Systems: 23rd International Conference, Nagoya, Japan, November 18?20, 2020, Proceedings, pages 19–33. In series: Lecture notes in artificial intelligence #12568. Springer. ISBN: 978-3-030-69322-0, 978-3-030-69321-3.
DOI: 10.1007/978-3-030-69322-0_2.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

We present, analyze and benchmark two algorithms for simultaneous coalition structure generation and assignment: one based entirely on dynamic programming, and one anytime hybrid approach that uses branch-and-bound together with dynamic programming. To evaluate the algorithms’ performance, we benchmark them against both CPLEX (an industry-grade solver) and the state-of-the-art using difficult randomized data sets of varying distribution and complexity. Our results show that our hybrid algorithm greatly outperforms CPLEX, pure dynamic programming and the current state-of-the-art in all of our benchmarks. For example, when solving one of the most difficult problem sets, our hybrid approach finds optimum in roughly 0.1% of the time that the current best method needs, and it generates 98% efficient interim solutions in milliseconds in all of our anytime benchmarks; a considerable improvement over what previous methods can achieve.

[669] Berggren Mathias and Sonesson Daniel. 2021.
Design Optimization in Gas Turbines using Machine Learning: A study performed for Siemens Energy AB.
Student Thesis. 56 pages. ISRN: LIU-IDA/LITH-EX-A-21/007--SE.

In this thesis, the authors investigate how machine learning can be utilized for speeding up the design optimization process of gas turbines. The Finite Element Analysis (FEA) steps of the design process are examined if they can be replaced with machine learning algorithms. The study is done using a component with given constraints that are provided by Siemens Energy AB. With this component, two approaches to using machine learning are tested. One utilizes design parameters, i.e. raw floating-point numbers, such as the height and width. The other technique uses a high dimensional mesh as input. It is concluded that using design parameters with surrogate models is a viable way of performing design optimization while mesh input is currently not. Results from using different amount of data samples are presented and evaluated.

[668] Patrick Doherty and Andrzej Szalas. 2021.
Rough set reasoning using answer set programs.
International Journal of Approximate Reasoning, 130(March):126–149. Elsevier.
DOI: 10.1016/j.ijar.2020.12.010.
Note: Funding: ELLIIT Network Organization for Information and Communication Technology, Sweden; Swedish Foundation for Strategic Research SSF(Smart Systems Project) [RIT15-0097]; Jinan University (Zhuhai Campus); National Science Centre PolandNational Science Centre, Poland [2017/27/B/ST6/02018]
Fulltext: https://doi.org/10.1016/j.ijar.2020.12.0...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Reasoning about uncertainty is one of the main cornerstones of Knowledge Representation. Formal representations of uncertainty are numerous and highly varied due to different types of uncertainty intended to be modeled such as vagueness, imprecision and incompleteness. There is a rich body of theoretical results that has been generated for many of these approaches. It is often the case though, that pragmatic tools for reasoning with uncertainty lag behind this rich body of theoretical results. Rough set theory is one such approach for modeling incompleteness and imprecision based on indiscernibility and its generalizations. In this paper, we provide a pragmatic tool for constructively reasoning with generalized rough set approximations that is based on the use of Answer Set Programming (Asp). We provide an interpretation of answer sets as (generalized) approximations of crisp sets (when possible) and show how to use Asp solvers as a tool for reasoning about (generalized) rough set approximations situated in realistic knowledge bases. The paper includes generic Asp templates for doing this and also provides a case study showing how these techniques can be used to generate reducts for incomplete information systems. Complete, ready to run clingo Asp code is provided in the Appendix, for all programs considered. These can be executed for validation purposes in the clingo Asp solver.

2020
[667] Jendrik Seipp, Samuel von Allmen and Malte Helmert. 2020.
Incremental Search for Counterexample-Guided Cartesian Abstraction Refinement.
In Proceedings of the 30th International Conference on Automated Planning and Scheduling.
Paper: https://ojs.aaai.org/index.php/ICAPS/art...

Counterexample-guided Cartesian abstraction refinement has been shown to yield informative heuristics for optimal classical planning. The algorithm iteratively finds an abstract solution and uses it to decide how to refine the abstraction. Since the abstraction grows in each step, finding solutions is the main bottleneck of the refinement loop. We cast the refinements as an incremental search problem and show that this drastically reduces the time for computing abstractions.

[666] Gabriele RŲger, Malte Helmert, Jendrik Seipp and Silvan Sievers. 2020.
An Atom-Centric Perspective on Stubborn Sets.
In Proceedings of the 13th Annual Symposium on Combinatorial Search.
Paper: https://ojs.aaai.org/index.php/SOCS/arti...

Stubborn sets are an optimality-preserving pruning technique for factored state-space search, for example in classical planning. Their applicability is limited by their computational overhead. We describe a new algorithm for computing stubborn sets that is based on the state variables of the state space, while previous algorithms are based on its actions. Typical factored state spaces tend to have far fewer state variables than actions, and therefore our new algorithm is much more efficient than the previous state of the art, making stubborn sets a viable technique in many cases where they previously were not.

[665] Jendrik Seipp, Thomas Keller and Malte Helmert. 2020.
Saturated Cost Partitioning for Optimal Classical Planning.
The journal of artificial intelligence research, 67(??):129–167. A A A I Press.
DOI: 10.1613/jair.1.11673.
Fulltext: https://doi.org/10.1613/jair.1.11673
Link: https://doi.org/10.1613/jair.1.11673
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Cost partitioning is a method for admissibly combining a set of admissible heuristic estimators by distributing operator costs among the heuristics. Computing an optimal cost partitioning, i.e., the operator cost distribution that maximizes the heuristic value, is often prohibitively expensive to compute. Saturated cost partitioning is an alternative that is much faster to compute and has been shown to yield high-quality heuristics. However, its greedy nature makes it highly susceptible to the order in which the heuristics are considered. We propose a greedy algorithm to generate orders and show how to use hill-climbing search to optimize a given order. Combining both techniques leads to significantly better heuristic estimates than using the best random order that is generated in the same time. Since there is often no single order that gives good guidance on the whole state space, we use the maximum of multiple orders as a heuristic that is significantly better informed than any single-order heuristic, especially when we actively search for a set of diverse orders.

[664] Oscar Bjurling, Rego Granlund, Jens Alfredson, Mattias Arvola and Tom Ziemke. 2020.
Drone Swarms in Forest Firefighting: A Local Development Case Study of Multi-Level Human-Swarm Interaction.
In Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society. Association for Computing Machinery (ACM). ISBN: 9781450375795.
DOI: 10.1145/3419249.3421239.

Swarms of autonomous and coordinating Unmanned Aerial Vehicles (UAVs) are rapidly being developed to enable simultaneous control of multiple UAVs. In the field of Human-Swarm Interaction (HSI), researchers develop and study swarm algorithms and various means of control and evaluate their cognitive and task performance. There is, however, a lack of research describing how UAV swarms will fit into future real-world domain contexts. To remedy this, this paper describes a case study conducted within the community of firefighters, more precisely two Swedish fire departments that regularly deploy UAVs in fire responses. Based on an initial description of how their UAVs are used in a forest firefighting context, participating UAV operators and unit commanders envisioned a scenario that showed how the swarm and its capabilities could be utilized given the constraints and requirements of a forest firefighting mission. Based on this swarm scenario description we developed a swarm interaction model that describes how the operators’ interaction traverses multiple levels ranging from the entire swarm, via subswarms and individual UAVs, to specific sensors and equipment carried by the UAVs. The results suggest that human-in-the-loop simulation studies need to enable interaction across multiple swarm levels as this interaction may exert additional cognitive strain on the human operator.

[663] Fredrik Pršntare, Mattias Tiger, David BergstrŲm, Herman Appelgren and Fredrik Heintz. 2020.
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms.
In .

This paper presents preliminary work on using deep neural networksto guide general-purpose heuristic algorithms for performing utilitarian combinatorial assignment. In more detail, we use deep learning in an attempt to produce heuristics that can be used together with e.g., search algorithms to generatefeasible solutions of higher quality more quickly. Our results indicate that ourapproach could be a promising future method for constructing such heuristics.

[662] Full text  Fredrik Pršntare and Fredrik Heintz. 2020.
An anytime algorithm for optimal simultaneous coalition structure generation and assignment.
Autonomous Agents and Multi-Agent Systems, 34(29):????. Springer-Verlag New York.
DOI: 10.1007/s10458-020-09450-1.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

An important research problem in artificial intelligence is how to organize multiple agents, and coordinate them, so that they can work together to solve problems. Coordinating agents in a multi-agent system can significantly affect the system‚Äôs performance‚ÄĒthe agents can, in many instances, be organized so that they can solve tasks more efficiently, and consequently benefit collectively and individually. Central to this endeavor is coalition formation‚ÄĒthe process by which heterogeneous agents organize and form disjoint groups (coalitions). Coalition formation often involves finding a coalition structure (an exhaustive set of disjoint coalitions) that maximizes the system‚Äôs potential performance (e.g., social welfare) through coalition structure generation. However, coalition structure generation typically has no notion of goals. In cooperative settings, where coordination of multiple coalitions is important, this may generate suboptimal teams for achieving and accomplishing the tasks and goals at hand. With this in mind, we consider simultaneously generating coalitions of agents and assigning the coalitions to independent alternatives (e.g., tasks/goals), and present an anytime algorithm for the simultaneous coalition structure generation and assignment problem. This combinatorial optimization problem has many real-world applications, including forming goal-oriented teams. To evaluate the presented algorithm‚Äôs performance, we present five methods for synthetic problem set generation, and benchmark the algorithm against the industry-grade solver CPLEX using randomized data sets of varying distribution and complexity. To test its anytime-performance, we compare the quality of its interim solutions against those generated by a greedy algorithm and pure random search. Finally, we also apply the algorithm to solve the problem of assigning agents to regions in a major commercial strategy game, and show that it can be used in game-playing to coordinate smaller sets of agents in real-time.

[661] Jenny Kunz and Marco Kuhlmann. 2020.
Classifier Probes May Just Learn from Linear Context Features.
In Proceedings of the 28th International Conference on Computational Linguistics, pages 5136–5146.

Classifiers trained on auxiliary probing tasks are a popular tool to analyze the representations learned by neural sentence encoders such as BERT and ELMo. While many authors are aware of the difficulty to distinguish between ‚Äúextracting the linguistic structure encoded in the representations‚ÄĚ and ‚Äúlearning the probing task,‚ÄĚ the validity of probing methods calls for further research. Using a neighboring word identity prediction task, we show that the token embeddings learned by neural sentence encoders contain a significant amount of information about the exact linear context of the token, and hypothesize that, with such information, learning standard probing tasks may be feasible even without additional linguistic structure. We develop this hypothesis into a framework in which analysis efforts can be scrutinized and argue that, with current models and baselines, conclusions that representations contain linguistic structure are not well-founded. Current probing methodology, such as restricting the classifier‚Äôs expressiveness or using strong baselines, can help to better estimate the complexity of learning, but not build a foundation for speculations about the nature of the linguistic structure encoded in the learned representations.

[660] Konrad K. Dabrowski, Peter Jonsson, Sebastian Ordyniak and George Osipov. 2020.
Fine-Grained Complexity of Temporal Problems.
In KR2020: Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, pages 284–293. IJCAI-INT JOINT CONF ARTIF INTELL. ISBN: 9780999241172.
DOI: 10.24963/kr.2020/29.
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; Swedish Research Council (VR)Swedish Research Council [2017-04112]

Expressive temporal reasoning formalisms are essential for AI. One family of such formalisms consists of disjunctive extensions of the simple temporal problem (STP). Such extensions are well studied in the literature and they have many important applications. It is known that deciding satisfiability of disjunctive STPs is NP-hard, while the fine-grained complexity of such problems is virtually unexplored. We present novel algorithms that exploit structural properties of the solution space and prove, assuming the Exponential-Time Hypothesis, that their worst-case time complexity is close to optimal. Among other things, we make progress towards resolving a long-open question concerning whether Allens interval algebra can be solved in single-exponential time, by giving a 2(O(n log log n)) algorithm for the special case of unit-length intervals.

[659] Barbara Dunin-Keplicz and Andrzej Szalas. 2020.
Shadowing in Many-Valued Nested Structures.
In 2020 IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL), pages 230–236. IEEE. ISBN: 9781728154077, 9781728154060, 9781728154053.
DOI: 10.1109/ISMVL49045.2020.00005.
Note: Funding: National Science Centre PolandNational Science Centre, Poland [2015/19/B/ST6/02589, 2017/27/B/ST6/02018]

Belief shadowing is a relatively recent approach to belief change. In essence, shadowing depends on accepting beliefs of others at the expense of dismissing, perhaps temporarily, some of the own ones. As a transient belief change, it is useful when an agent, acting as a group member or playing a particular role, has to adopt adequate \"external\" beliefs. So far two forms of shadowing, single and multiple, have been considered. While the former specifies shadowing when an agent belongs to a single group or plays a single role, multiple shadowing relaxes this restriction.In the paper we generalize shadowing to arbitrary finitely many-valued logics and consider more complex semantical structures allowing arbitrarily nested sets of worlds. We show that in this general setting multiple shadowing can be represented by single shadowing. The complexity of queries involving such generic shadowing operators is also analyzed.

[658] Full text  Johan KšllstrŲm and Fredrik Heintz. 2020.
Agent Coordination in Air Combat Simulation using Multi-Agent Deep Reinforcement Learning.
In In proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 2157–2164. IEEE conference proceedings. ISBN: 9781728185279, 9781728185262.
DOI: 10.1109/SMC42975.2020.9283492.
Note: Funding: Swedish Governmental Agency for Innovation SystemsVinnova [NFFP7/2017-04885]; Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation
Proceedings of the 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC): https://ieeexplore.ieee.org/xpl/conhome/...
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Simulation-based training has the potential to significantly improve training value in the air combat domain. However, synthetic opponents must be controlled by high-quality behavior models, in order to exhibit human-like behavior. Building such models by hand is recognized as a very challenging task. In this work, we study how multi-agent deep reinforcement learning can be used to construct behavior models for synthetic pilots in air combat simulation. We empirically evaluate a number of approaches in two air combat scenarios, and demonstrate that curriculum learning is a promising approach for handling the high-dimensional state space of the air combat domain, and that multi-objective learning can produce synthetic agents with diverse characteristics, which can stimulate human pilots in training.

[657] Linda Mannila and Lars-Ňke Nordťn. 2020.
Att undervisa textbaserad programmering i skolan.
Book. Studentlitteratur. 256 pages. ISBN: 9789144130644.
Note: Upplaga 1
Link: http://libris.kb.se/bib/1d5q2kllzjq18z3v

[656] Andrť Willquist. 2020.
Uncertainty Discretization for Motion Planning Under Uncertainty.
Student Thesis. 55 pages. ISRN: LIU-IDA/LITH-EX-A--20/060--SE.

In this thesis, the problem of motion planning under uncertainty is explored. Motion planning under uncertainty is important since even with noise during the execution of the plan, it is desirable to keep the collision risk low. However, for the motion planning to be useful it needs to be possible to perform it in a reasonable time. The introduction of state uncertainty leads to a substantial increase in search time due to the additional dimensions it adds to the search space. In order to alleviate this problem, different approaches to pruning of the search space are explored. The initial approach is to prune states based on having strictly worse uncertainty and path cost than other found states. Having performed this initial pruning, an alternate approach to comparing uncertainties is examined in order to explore if it is possible to achieve a lower search time. The approach taken in order to lower the search time further is to discretize the covariance of a state by using a number of buckets. However, this discretization results in giving up the completeness and optimality of the algorithm. Having implemented these different ways of pruning, their performance is tested on a number of different scenarios. This is done by evaluating the planner using the pruning in several different scenarios including uncertainty and one without uncertainty. It is found that all of the pruning approaches reduce the overall search time compared to when no additional pruning based on the uncertainty is done. Additionally, it is indicated that the bucket-based approach reduce the search time to a greater extent than the strict pruning approach. Furthermore, the extensions made results in no increase in cost or a very small increase in cost for the explored scenarios. Based on these results, it is likely that the bucket pruning approach has some potential. However more studies, particularly with additional scenarios, needs to be made before any definitive conclusions can be made.

[655] Veronika Domova, Erik Gšrtner, Fredrik Pršntare, Martin Pallin, Johan KšllstrŲm and Nikita Korzhitskii. 2020.
Improving Usability of Search and Rescue Decision Support Systems: WARA-PS Case Study.
In In proceedings of the 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), pages 1251–1254. In series: IEEE International Conference on Emerging Technologies and Factory Automation #25. IEEE conference proceedings. ISBN: 9781728189574, 9781728189567.
DOI: 10.1109/ETFA46521.2020.9211980.
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation
Proceedings of the 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA): https://ieeexplore.ieee.org/xpl/conhome/...
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Novel autonomous search and rescue systems, although powerful, still require a human decision-maker involvement. In this project, we focus on the human aspect of one such novel autonomous SAR system. Relying on the knowledge gained in a field study, as well as through the literature, we introduced several extensions to the system that allowed us to achieve a more user-centered interface. In the evaluation session with a rescue service specialist, we received positive feedback and defined potential directions for future work.

[654] Barbara Dunin-Keplicz and Andrzej Szalas. 2020.
A Framework for Organization-Centered Doxastic Reasoning.
In Matteo Cristani, Carlos Toro, Cecilia Zanni-Merk, Robert J. Howlett, Lakhmi C. Jain, editors, 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, pages 3019–3028. In series: Procedia Computer Science #176. Elsevier.
DOI: 10.1016/j.procs.2020.09.201.
Fulltext: https://doi.org/10.1016/j.procs.2020.09....

[653] Andrzej Szalas. 2020.
Revisiting Object-Rule Fusion in Query Languages.
In Matteo Cristani, Carlos Toro, Cecilia Zanni-Merk, Robert J. Howlett, Lakhmi C. Jain, editors, 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems. In series: Procedia Computer Science #176. Elsevier.
DOI: 10.1016/j.procs.2020.08.006.
Fulltext: https://doi.org/10.1016/j.procs.2020.08....

[652] Andrť Willquist. 2020.
Uncertainty Discretization for Motion Planning Under Uncertainty.
Student Thesis. 55 pages. ISRN: LIU-IDA/LITH-EX-A--20/060--SE.

In this thesis, the problem of motion planning under uncertainty is explored.Motion planning under uncertainty is important since even with noise during the execution of the plan, it is desierable to keep the collision risk low.However, for the motion planning to be useful it needs to be possible to perform it in a reasonable time.The introduction of state uncertainty leads to a substantial increase in search time due to the additional dimensions it adds to the search space.In order to alleviate this problem, different approaches to pruning of the search space are explored.The initial approach is to prune states based on having strictly worse uncertainty and path cost than other found states.Having performed this initial pruning, an alternate approach to comparing uncertainties is examined in order to explore if it is possible to achieve a lower search time. The approach taken in order to lower the search time further is to discretize the covariance of a state by using a number of buckets.However, this discretization results in giving up the completeness and optimality of the algorithm.Having implemented these different ways of pruning, their performance is tested on a number of different scenarios.This is done by evaluating the planner using the pruning in several different scenarios including uncertainty and one without uncertainty.It is found that all of the pruning approaches reduce the overall search time compared to when no additional pruning based on the uncertainty is done.Additionally, it is indicated that the bucket based approach reduce the search time to a greater extent than the strict pruning approach.Furthermore, the extensions made results in no increase in cost or a very small increase in cost for the explored scenarios.Based on these results, it is likely that the bucket pruning approach has some potential.However more studies, perticularly with additional scenarios, needs to be made before any definitive conclusions can be made.

[651] Zacharias NordstrŲm. 2020.
Extracting Behaviour Trees from Deep Q-Networks: Using learning from demostration to transfer knowledge between models.
Student Thesis. 54 pages. ISRN: LIU-IDA/LITH-EX-A--20/059‚ÄĒSE.

In recent years the advancement in machine learning have solved more and more complex problems. But still these techniques are not commonly used in the industry. One problem is that many of the techniques are black boxes, it is hard to analyse them to make sure that their behaviour is safe. This property makes them unsuitable for safety critical systems. The goal of this thesis is to examine if the deep learning technique Deep Q-network could be used to create a behaviour tree that can solve the same problem. A behaviour tree is a tree representation of a flow structure that is used for representing behaviours, often used in video games or robotics. To solve the problem two simulators are used, one models a cart that shall balance a pole called cart pole, the other is a static world which needs to be navigated called grid world. Inspiration is taken from the learning from demonstration field to use the Deep Q-network as a teacher and then create a decision tree. During the creation of the decision tree two attributes are used for pruning; to look at the trees accuracy or performance. The thesis then compare three techniques, called Naive, BT Espresso, and BT Espresso Simplified. The techniques are used to transform the extracted decision tree into a behaviour tree. When it comes to the performance of the created behaviour trees they all manage to complete the simulator scenarios in the same, or close to, capacity as the trained Deep Q-network. The trees created from the performance pruned decision tree are generally smaller and less complex, but they have worse accuracy. For cart pole the trees created from the accuracy pruned tree has around 10 000 nodes but the performance pruned trees have around 10-20 nodes. The difference in grid world is smaller going from 35-45 nodes to 40-50 nodes. To get the smallest tree with the best performance then the performance pruned tree should be used with the BT Espresso Simplified algorithm. This thesis have shown that it is possible to use knowledge from a trained Deep Q-network model to create a Behaviour tree that can complete the same task.

[650] Karol Wojtulewicz and Viktor Agbrink. 2020.
Evaluating DCNN architecturesfor multinomial area classicationusing satellite data.
Student Thesis. ISRN: LIU-IDA/LITH-EX-A--20/031--SE.

The most common approach to analysing satellite imagery is building or object segmentation,which expects an algorithm to find and segment objects with specific boundaries thatare present in the satellite imagery. The company Vricon takes satellite imagery analysisfurther with the goal of reproducing the entire world into a 3D mesh. This 3D reconstructionis performed by a set of complex algorithms excelling in different object reconstructionswhich need sufficient labeling in the original 2D satellite imagery to ensure validtransformations. Vricon believes that the labeling of areas can be used to improve the algorithmselection process further. Therefore, the company wants to investigate if multinomiallarge area classification can be performed successfully using the satellite image data availableat the company. To enable this type of classification, the company’s gold-standarddataset containing labeled objects such as individual buildings, single trees, roads amongothers, has been transformed into an large area gold-standard dataset in an unsupervisedmanner. This dataset was later used to evaluate large area classification using several stateof-the-art Deep Convolutional Neural Network (DCNN) semantic segmentation architectureson both RGB as well as RGB and Digital Surface Model (DSM) height data. Theresults yield close to 63% mIoU and close to 80% pixel accuracy on validation data withoutusing the DSM height data in the process. This thesis additionally contributes with a novelapproach for large area gold-standard creation from existing object labeled datasets.

[649] Andrzej Szalas. 2020.
On the Probability and Cost of Ignorance, Inconsistency, Nonsense and More.
Journal of Multiple-Valued Logic and Soft Computing, 34(5-6):423–450. Old City Publishing.
Note: Funding agencies:  National Science Centre PolandNational Science Center, PolandNational Science Centre, Poland [2017/27/B/ST6/02018]
Journal home page: https://www.oldcitypublishing.com/journa...

Ignorance, inconsistency, nonsense and similar phenomena are omnipresent in everyday reasoning. They have been intensively studied, especially in the area of multiple-valued logics. Therefore we develop a framework for belief bases, combining multiple-valued and probabilistic reasoning, with the main focus on the way belief bases are actually used and accessed through queries.As an implementation tool we use a probabilistic programming language PROBLOG. Though based on distribution semantics with the independence assumption, we show how its constructs can successfully be used in implementing the considered logics and belief bases. In particular, we develop a technique for shifting probabilistic dependencies to the level of symbolic parts of belief bases.We also discuss applications of the framework in reasoning with Likert-type scales, widely exploited in questionnaire-based experimental research in psychology, economics, sociology, politics, public opinion measurements, and related areas.

[648] Patrick Doherty and Andrzej Szalas. 2020.
Rough Forgetting.
In Rough Sets. IJCRS 2020, pages 3–18. In series: Lecture Notes in Computer Science #12179. Springer. ISBN: 9783030527051, 9783030527044.
DOI: 10.1007/978-3-030-52705-1_1.
Note: ELLIIT Network Organization for Information and Communication Technology, Sweden; Swedish Foundation for Strategic Research SSFSwedish Foundation for Strategic Research; Jinan University (Zhuhai Campus) [2017/27/B/ST6/02018]; National Science Centre PolandNational Science Centre, Poland
Fulltext: https://doi.org/10.1007/978-3-030-52705-...

Recent work in the area of Knowledge Representation and Reasoning has focused on modification and optimization of knowledge bases (KB) through the use of forgetting operators of the form forget(KB, (R) over bar), where (R) over bar is a set of relations in the language signature used to specify the KB. The result of this operation is a new KB where the relations in (R) over bar are removed from the KB in a principled manner resulting in a more efficient representation of the KB for different purposes. The forgetting operator is also reflected semantically in terms of the relation between the original models of the KB and the models for the revised KB after forgetting. In this paper, we first develop a rough reasoning framework where our KBs consist of rough formulas with a semantics based on a generalization of Kleene algebras. Using intuitions from the classical case, we then define a forgetting operator that can be applied to rough KBs removing rough relations. A constructive basis for generating a new KB as the result of applying the forgetting operator to a rough KB is specified using second-order quantifier elimination techniques. We show the application of this technique with some practical examples.

[647] Andrzej Szalas. 2020.
A Paraconsistent ASP-like Language with Tractable Model Generation.
Journal of Applied Logics - IfCoLog Journal of Logic and Applications, 7(3):361–389. College Publications.
Note: Funding agencies: This work has been supported by grant 2017/27/B/ST6/02018 of the National Science Centre Poland.
Link to article: http://www.collegepublications.co.uk/dow...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Answer Set Programming (ASP) is nowadays a dominant rule-based knowledge representation tool. Though existing ASP variants enjoy efficient implementations, generating an answer set remains intractable. The goal of this research is to define a new ASP-like rule language, 4SP, with tractable model generation. The language combines ideas of ASP and a paraconsistent rule language 4QL. Though 4SP shares the syntax of ASP and for each program all its answer sets are among 4SP models, the new language differs from ASP in its logical foundations, the intended methodology of its use and complexity of computing models. As we show in the paper, 4QL can be seen as a paraconsistent counterpart of ASP programs stratified with respect to default negation. Although model generation for 4QL programs is tractable, dropping stratification makes it intractable for both 4QL and ASP. To retain tractability while allowing non-stratified programs, in 4SP we introduce trial expressions interlacing programs with hypotheses as to the truth values of default negations. This allows us to develop a model generation algorithm with deterministic polynomial time complexity. We also show relationships among 4SP, ASP and 4QL.

[646] Full text  Mattias Tiger and Fredrik Heintz. 2020.
Spatio-Temporal Learning, Reasoning and Decision-Making with Robot Safety Applications: PhD Research Project Extended Abstract.
In Fredrik Johansson, editor, Proceedings of the 32nd annual workshop of the Swedish Artificial Intelligence Society (SAIS 2020).

Cyber-physical systems such as robots and intelligent transportation systems are heavy producers and consumers of trajectory data. Making sense of this data and putting it to good use is essential for such systems. When industrial robots, intelligent vehicles and aerial drones are intended to co-exist, side-by-side, with people in human-tailored environments safety is paramount. Safe operations require uncertainty-aware motion pattern recognition, incremental reasoning and rapid decision-making to manage collision avoidance, monitor movement execution and detect abnormal motion. We investigate models and techniques that can support and leverage the interplay between these various trajectory-based capabilities to improve the state-of-the-art for intelligent autonomous systems.

[645] Jonas Lundberg and BjŲrn Johansson. 2020.
A framework for describing interaction between human operators and autonomous, automated, and manual control systems.
Cognition, Technology & Work, ??(??):????. SPRINGER LONDON LTD.
DOI: 10.1007/s10111-020-00637-w.
Publication status: Epub ahead of print
Note: Funding Agencies|Linkoping University - Swedish Transport Administration; Air Navigation Services of Sweden
fulltext:print: http://liu.diva-portal.org/smash/get/div...

This paper addresses how to describe critical episodes of interaction between human operators and autonomous, automated, and manual control systems. The first part of the paper poses three questions: (1) what levels of cognitive control are important to include in a descriptive framework for joint human-autonomy in process control; (2) how should one describe temporal developments in joint socio-technical systems; and (3) how does one analyse communication and control at the system joints. The paper proceeds by proposing a new framework for description and analysis, the Joint Control Framework (JCF), with a simple notation, the Score (JCF-S). It allows descriptions of the three previously mentioned aspects through three analytical activities: process mapping (PM), analysis of Levels of Autonomy in Cognitive Control (LACC), and temporal descriptions of human-machine interaction (T-HMI) through the Score notation. This facilitates analyses across cases and domains. The framework is discussed based on an analysis of two episodes; one work episode (from an air traffic control tower simulator); and one work procedure (from an unmanned traffic management system design concept).

[644] Marc Pŗmies Massip. 2020.
Multilingual identification of offensive content in social media.
Student Thesis. 50 pages. ISRN: LIU-IDA/LITH-EX-A--20/053--SE.

In today’s society there is a large number of social media users that are free to express their opinion on shared platforms. The socio-cultural differences between the people behind those accounts (in terms of ethnicity, gender, sexual orientation, religion, politics, . . . ) give rise to an important percentage of online discussions that make use of offensive language, which often affects in a negative way the psychological well-being of the victims. In order to address the problem, the endless stream of user-generated content engenders a need to find an accurate and scalable solution to detect offensive language using automated methods. This thesis explores different approaches to the offensiveness detection task focusing on five different languages: Arabic, Danish, English, Greek and Turkish. The results obtained using Support Vector Machines (SVM), Convolutional Neural Networks (CNN) and the Bidirectional Encoder Representations from Transformers (BERT) are compared, achieving state-of-the-art results with some of the methods tested. The effect of the embeddings used, the dataset size, the class imbalance percentage and the addition of sentiment features are studied and analysed, as well as the cross-lingual capabilities of pre-trained multilingual models.

[643] Samuel Blomqvist and BjŲrn Detterfelt. 2020.
Real Time Integrated Tools for Video Game Development: a usability study.
Student Thesis. 78 pages. ISRN: LIU-IDA/LITH-EX-A--20/050--SE.

The video game industry can be ruthless. As a developer, you usually find yourself working in the popular third-party development tools of the time. These tools however might not provide the best usability and quality of life one desires. This can lead to a lot of frustration for the developer, especially when the development enters a crunch period of long and hard work. We believe some of the frustration can be avoided, and we believe this can be done by creating effective, functional and user-friendly integrated development tools specialized for the development environment. In this master's thesis we investigated just that, how integrated game development tools can be designed to be usable in terms of effectiveness and learnability. The investigation was performed by designing and implementing an integrated game development tool. The development of the tool was performed iteratively with user testing between every iteration to find usability defects, allowing the tool to be refined and improved throughout the development process. To finish off the development process, there was a final user test where professional video game developers tried out the tool and then answered a System Usability Scale questionnaire. The System Usability Scale score and task completion rate showed that the final state of the tool can be considered highly usable in terms of effectiveness and averagely usable in terms of learnability. This suggests that involving user testing in the development process is vital for ensuring good usability in the end product.

[642] Pia LÝtvedt. 2020.
Implementation of visualizations using a server-client architecture: Effects on performance measurements.
Student Thesis. 10 pages. ISRN: LIU-IDA/LITH-EX-G--20/052--SE.

Visualizing large datasets poses challenges in terms of how to create visualization applications with good performance. Due to the amount of data, transfer speed and processing speed may lead to waiting times that cause users to abandon the application. It is therefore important to select methods and techniques that can handle the data in as efficient a way as possible. The aim of this study was to investigate if a server-client architecture had better performance in a visualization web application than a purely client-side architecture in terms of selected performance metrics and network load, and whether the selection of implementation language and tools affected the performance of the server-client architecture implementation. To answer these questions, a visualization application was implemented in three different ways: a purely client-side implementation, a server-client implementation using Node.js for the server, and a server-client implementation using Flask for the server. The results showed that the purely client-side architecture suffered from a very long page loading time and high network load but was able to process data quickly in response to user actions in the application. The server-client architecture implementations could load the page faster, but responding to requests took longer, whereas the amount of data transferred was much lower. Furthermore, the server-client architecture implemented with a Node.js server performed better on all metrics than the application implemented with a Flask server. Overall, when taking all measurements into consideration, the Node.js server architecture may be the best choice among the three when working with a large dataset, although the longer response time compared to the purely client-side architecture may cause the application to seem less responsive.

[641] Full text  Johan KšllstrŲm and Fredrik Heintz. 2020.
Learning Agents for Improved Efficiency and Effectiveness in Simulation-Based Training.
In Poceedings of the 32nd annual workshop of the†Swedish Artificial Intelligence Society†(SAIS), pages 1–2.
Konferensens fulltext: https://www.chalmers.se/SiteCollectionDo...

Team training in complex domains often requires a substantial amount of resources, e.g., instructors, role-players and vehicles. For this reason, it may be difficult to realize efficient and effective training scenarios in a real-world setting. Instead, intelligent agents can be used to construct synthetic, simulationbased training environments. However, building behavior models for such agents is challenging, especially for the end-users of the training systems, who typically do not have expertise in artificial intelligence. In this PhD project, we study how machine learning can be used to simplify the process of constructing agents for simulation-based training. As a case study we use a simulation-based air combat training system. By constructing smarter synthetic agents the dependency on human training providers can be reduced, and the availability as well as the quality of training can be improved.

[640] Sebastian Lundqvist and Oliver Ekstrand. 2020.
Evaluating an ARCore application to get an image of the state of AR technology today.
Student Thesis. 8 pages. ISRN: LIU-IDA/LITH-EX-G--20/051--SE.

Augmented reality is an old technology that is still far away from being perfect. It is also quickly being improved upon and the state of AR today has come a long way from AR just a couple of years ago. New big players have recently introduced their tools and have made it easier than ever to develop AR applications. In this study we look at what established methods (if any) there are for AR evaluation, develop AR evaluation methods that fit our needs, carry out the evaluation and analyze the collected data. We also note some important things to think about when working with AR to increase tracking and recognition stability. The recommendations are: try to have reference images with high scores, have reference objects that are distinct enough from one another to not be mixed up and make sure that the visual for the reference image matches the visual for the reference object in its intended viewing environment.

[639] Per Olin. 2020.
Evaluation of text classification techniques for log file classification.
Student Thesis. 48 pages. ISRN: LIU-IDA/LITH-EX-A--20/048--SE.

System log files are filled with logged events, status codes, and other messages. By analyzing the log files, the systems current state can be determined, and find out if something during its execution went wrong. Log file analysis has been studied for some time now, where recent studies have shown state-of-the-art performance using machine learning techniques. In this thesis, document classification solutions were tested on log files in order to classify regular system runs versus abnormal system runs. To solve this task, supervised and unsupervised learning methods were combined. Doc2Vec was used to extract document features, and Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) based architectures on the classification task. With the use of the machine learning models and preprocessing techniques the tested models yielded an f1-score and accuracy above 95% when classifying log files.

[638] Oscar Lundblad. 2020.
The autonomous crewmate: A sociotechnical perspective to implementation of autonomous vehicles in sea rescue.
Student Thesis. 72 pages. ISRN: LIU-IDA/KOGVET-A--20/009--SE.

The usage of autonomous vehicles is starting to appear in several different domains and the domain of public safety is no exception. Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) has created a research arena for public safety (WARA-PS) to explore experimental features, usages, and implementation of autonomous vehicles within the domain of public safety. Collaborating in the arena are several companies, universities, and researchers. This thesis examines, in collaboration with Combitech, a company partnered in WARA-PS, how the implementation of autonomous vehicles affects the sociotechnical system of a search and rescue operation during a drifting boat with potential castaways. This is done by creating a case together with domain experts, analyzing the sociotechnical system within the case using cognitive work analysis and then complementing the analyses with the unmanned autonomous vehicles of WARA-PS. This thesis has shown how the WARA-PS vehicles can be implemented in the case of a drifting boat with potential castaways and how the implementation affects the sociotechnical system. Based on the analyses and opinions of domain experts’ future guidelines has been derived to further the work with sociotechnical aspects in WARA-PS.

[637] Viktor Brandt and Jesper Olofsson. 2020.
UndersŲkning av flexibel implementation fŲr hantering av multipla rŲsttjšnster.
Student Thesis. 12 pages. ISRN: LIU-IDA/LITH-EX-G--20/021--SE.

Att välja vilken eller vilka röststyrningstjänster man som företag vill stödja kan i dagens läge vara ett svårt val att göra. Det kan även var så att man inte har resurser att göra två olika implementationer. I den här undersökningen tittar vi på om det finns ett bra sätt att göra en implementation som kan hantera fler än en röststyrningstjänst. Tjänsterna vi har fokuserat på i undersökningen är Amazon Alexa och Google Assistant.

[636] Full text  Johan KšllstrŲm. 2020.
Adaptive Agent-Based Simulation for Individualized Training.
In B. An, N. Yorke-Smith, A. El Fallah Seghrouchni, G. Sukthankar, editors, Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 2193–2195. In series: International Conference on Autonomous Agents and Multiagent Systems #19. International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). ISBN: 978-1-4503-7518-4.
Link: http://www.ifaamas.org/Proceedings/aamas...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Agent-based simulation can be used for efficient and effective training of human operators and decision-makers. However, constructing realistic behavior models for the agents is challenging and time-consuming, especially for subject matter experts, who may not have expertise in artificial intelligence. In this work, we investigate how machine learning can be used to adapt simulation contents to the current needs of individual trainees. Our initial results demonstrate that multi-objective multi-agent reinforcement learning is a promising approach for creating agents with diverse and adaptive characteristics, which can stimulate humans in training.

[635] Arvid Edenheim. 2020.
Using Primary Dynamic Factor Analysis on repeated cross-sectional surveys with binary responses.
Student Thesis. 54 pages. ISRN: LIU-IDA/LITH-EX-A--20/007--SE.

With the growing popularity of business analytics, companies experience an increasing need of reliable data. Although the availability of behavioural data showing what the consumers do has increased, the access to data showing consumer mentality, what the con- sumers actually think, remain heavily dependent on tracking surveys. This thesis inves- tigates the performance of a Dynamic Factor Model using respondent-level data gathered through repeated cross-sectional surveys. Through Monte Carlo simulations, the model was shown to improve the accuracy of brand tracking estimates by double digit percent- ages, or equivalently reducing the required amount of data by more than a factor 2, while maintaining the same level of accuracy. Furthermore, the study showed clear indications that even greater performance benefits are possible.

[634] Olov Andersson. 2020.
Learning to Make Safe Real-Time Decisions Under Uncertainty for Autonomous Robots.
PhD Thesis. In series: LinkŲping Studies in Science and Technology. Dissertations #2051. LinkŲping University Electronic Press. 55 pages. ISBN: 9789179298890.
DOI: 10.3384/diss.diva-163419.
Fulltext: https://doi.org/10.3384/diss.diva-163419
preview image: http://liu.diva-portal.org/smash/get/div...

Robots are increasingly expected to go beyond controlled environments in laboratories and factories, to act autonomously in real-world workplaces and public spaces. Autonomous robots navigating the real world have to contend with a great deal of uncertainty, which poses additional challenges. Uncertainty in the real world accrues from several sources. Some of it may originate from imperfect internal models of reality. Other uncertainty is inherent, a direct side effect of partial observability induced by sensor limitations and occlusions. Regardless of the source, the resulting decision problem is unfortunately computationally intractable under uncertainty. This poses a great challenge as the real world is also dynamic. It will not pause while the robot computes a solution. Autonomous robots navigating among people, for example in traffic, need to be able to make split-second decisions. Uncertainty is therefore often neglected in practice, with potentially catastrophic consequences when something unexpected happens. The aim of this thesis is to leverage recent advances in machine learning to compute safe real-time approximations to decision-making under uncertainty for real-world robots. We explore a range of methods, from probabilistic to deep learning, as well as different combinations with optimization-based methods from robotics, planning and control. Driven by applications in robot navigation, and grounded in experiments with real autonomous quadcopters, we address several parts of this problem. From reducing uncertainty by learning better models, to directly approximating the decision problem itself, all the while attempting to satisfy both the safety and real-time requirements of real-world autonomy.

[633] Full text  Fredrik Pršntare and Fredrik Heintz. 2020.
An anytime algorithm for optimal simultaneous coalition structure generation and assignment.
Autonomous Agents and Multi-Agent Systems, 34(1):????. SPRINGER.
DOI: 10.1007/s10458-020-09450-1.
Note: Funding Agencies|Linkoping University; Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation
fulltext:print: http://liu.diva-portal.org/smash/get/div...

An important research problem in artificial intelligence is how to organize multiple agents, and coordinate them, so that they can work together to solve problems. Coordinating agents in a multi-agent system can significantly affect the systems performance-the agents can, in many instances, be organized so that they can solve tasks more efficiently, and consequently benefit collectively and individually. Central to this endeavor is coalition formation-the process by which heterogeneous agents organize and form disjoint groups (coalitions). Coalition formation often involves finding a coalition structure (an exhaustive set of disjoint coalitions) that maximizes the systems potential performance (e.g., social welfare) through coalition structure generation. However, coalition structure generation typically has no notion of goals. In cooperative settings, where coordination of multiple coalitions is important, this may generate suboptimal teams for achieving and accomplishing the tasks and goals at hand. With this in mind, we consider simultaneously generating coalitions of agents and assigning the coalitions to independent alternatives (e.g., tasks/goals), and present an anytime algorithm for the simultaneous coalition structure generation and assignment problem. This combinatorial optimization problem hasmany real-world applications, including forming goal-oriented teams. To evaluate the presented algorithms performance, we present five methods for synthetic problem set generation, and benchmark the algorithm against the industry-grade solver CPLEXusing randomized data sets of varying distribution and complexity. To test its anytime-performance, we compare the quality of its interim solutions against those generated by a greedy algorithm and pure random search. Finally, we also apply the algorithm to solve the problem of assigning agents to regions in a major commercial strategy game, and show that it can be used in game-playing to coordinate smaller sets of agents in real-time.

[632] Per-Magnus Olsson and Kaj Holmberg. 2020.
Exploiting parallelization and synergy in derivative free optimization.
Technical Report. In series: LiTH-MAT-R #2020:4. LinkŲping University Electronic Press. 18 pages.

Real life optimization often concerns difficult objective functions, in two aspects, namely that gradients are unavailable, and that evaluation of the objective function takes a long time. Such problems are often attacked with model building algorithms, where an approximation of the function is constructed and solved, in order to find a new promising point to evaluate. We study several ways of saving time by using parallel calculations in the context of model building algorithms, which is not trivial, since such algorithms are inherently sequential. We present a number of ideas that has been implemented and tested on a large number of known test functions, and a few new ones. The computational results reveal that some ideas are quite promising.

[631] Full text  Mattias Tiger and Fredrik Heintz. 2020.
Incremental Reasoning in Probabilistic Signal Temporal Logic.
International Journal of Approximate Reasoning, 119(??):325–352. Elsevier.
DOI: 10.1016/j.ijar.2020.01.009.
Note: Funding agencies: National Graduate School in Computer Science, Sweden (CUGS); Swedish Research Council (VR) Linnaeus Center CADICSSwedish Research Council; ELLIIT Excellence Center at Linkoping-Lund for Information Technology; Wallenberg AI, Autonomous Systems and Softwar
Fulltext: https://doi.org/10.1016/j.ijar.2020.01.0...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Robot safety is of growing concern given recent developments in intelligent autonomous systems. For complex agents operating in uncertain, complex and rapidly-changing environments it is difficult to guarantee safety without imposing unrealistic assumptions and restrictions. It is therefore necessary to complement traditional formal verification with monitoring of the running system after deployment. Runtime verification can be used to monitor that an agent behaves according to a formal specification. The specification can contain safety-related requirements and assumptions about the environment, environment-agent interactions and agent-agent interactions. A key problem is the uncertain and changing nature of the environment. This necessitates requirements on how probable a certain outcome is and on predictions of future states. We propose Probabilistic Signal Temporal Logic (ProbSTL) by extending Signal Temporal Logic with a sub-language to allow statements over probabilities, observations and predictions. We further introduce and prove the correctness of the incremental stream reasoning technique progression over well-formed formulas in ProbSTL. Experimental evaluations demonstrate the applicability and benefits of ProbSTL for robot safety.

[630] Filip StrŲmbšck, Linda Mannila and Mariam Kamkar. 2020.
Exploring Students? Understanding of Concurrency: A Phenomenographic Study.
In Proceedings of†SIGCSE ?20. ACM Publications. ISBN: 978-1-4503-6793-6.
DOI: 10.1145/3328778.3366856.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

This paper continues previous efforts in understanding the problemsstudents face when learning concurrency. In this paper, weexplore students’ understanding of the subject using phenomenographyin order to gain insights that can aid in explaining the underlyingcauses for common student mistakes in concurrency, whichhas been studied in depth previously. Students’ experience of concurrencyand critical sections were analyzed using a phenomenographicstudy based on interviews with students attending one oftwo courses on concurrency and operating systems. We present6 categories describing students’ experience of concurrency, and4 categories describing students’ experience of critical sections inthis paper. Furthermore, these categories are related to previousresults, both to explore how misconceptions in the categores relateto student mistakes and to estimate how common it is for eachcategory to be discerned.

[629] Olov Andersson, Per Sidťn, Johan Dahlin, Patrick Doherty and Mattias Villani. 2020.
Real-Time Robotic Search using Structural Spatial Point Processes.
In 35TH UNCERTAINTY IN ARTIFICIAL INTELLIGENCE CONFERENCE (UAI 2019), pages 995–1005. In series: Proceedings of Machine Learning Research (PMLR) #115. Association For Uncertainty in Artificial Intelligence (AUAI).
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP); WASP Autonomous Research Arenas - Knut and Alice Wallenberg Foundation; Swedish Foundation for Strategic Research (SSF)Swedish Foundation for Strategic Research; ELLIIT Excellence Center at Link opingLund for Information Technology
Link: http://auai.org/uai2019/proceedings/pape...

Aerial robots hold great potential for aiding Search and Rescue (SAR) efforts over large areas, such as during natural disasters. Traditional approaches typically search an area exhaustively, thereby ignoring that the density of victims varies based on predictable factors, such as the terrain, population density and the type of disaster. We present a probabilistic model to automate SAR planning, with explicit minimization of the expected time to discovery. The proposed model is a spatial point process with three interacting spatial fields for i) the point patterns of persons in the area, ii) the probability of detecting persons and iii) the probability of injury. This structure allows inclusion of informative priors from e.g. geographic or cell phone traffic data, while falling back to latent Gaussian processes when priors are missing or inaccurate. To solve this problem in real-time, we propose a combination of fast approximate inference using Integrated Nested Laplace Approximation (INLA), and a novel Monte Carlo tree search tailored to the problem. Experiments using data simulated from real world Geographic Information System (GIS) maps show that the framework outperforms competing approaches, finding many more injured in the crucial first hours.

2019
[628] Mariusz Wzorek, Cyrille Berger and Patrick Doherty. 2019.
Router Node Placement in Wireless Mesh Networks for Emergency Rescue Scenarios.
In PRICAI 2019: TRENDS IN ARTIFICIAL INTELLIGENCE, PT II, pages 496–509. In series: Lecture Notes in Artificial Intelligence #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-030-29911-8, 978-3-030-29910-1.
DOI: 10.1007/978-3-030-29911-8_38.
Note: Funding Agencies|ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [RIT 15-0097]; Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations. The general idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers. These kits will then be used in the generation of ad hoc Wireless Mesh Networks. A fundamental problem, known as the Router Node Placement problem (RNP) is to determine how one can optimally place such routers. An extended version of the RNP problem is specified that takes into account additional constraints that arise in actual field usage. This extended problem is solved with a new algorithm, RRT-WMN, based on a novel use of the Rapidly Exploring Random Trees (RRT) algorithm used in motion planning. A comparative empirical evaluation between RRT-WMN and existing techniques, CMA-ES and PSO, shows that the RRT-WMN algorithm has far better performance both in time and coverage as the extended RNP problem scales to realistic scenarios.

[627] Piotr Rudol and Patrick Doherty. 2019.
Evaluation of Human Body Detection Using Deep Neural Networks with Highly Compressed Videos for UAV Search and Rescue Missions.
In PRICAI 2019: TRENDS IN ARTIFICIAL INTELLIGENCE, PT III, pages 402–417. In series: Lecture Notes in Artificial Intelligence #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-030-29894-4, 978-3-030-29893-7.
DOI: 10.1007/978-3-030-29894-4_33.
Note: Funding Agencies|ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research (SymbiKBot Project); Wallenberg AI, Autonomous Systems and Software Program (WASP) - Research Arena Public Safety (WARA-PS)

Dealing with compressed video streams in mobile robotics is an unavoidable fact of life. Transferring images between mobile robots or to the Cloud using wireless links can practically only be achieved using lossy video compression. This introduces artifacts that often make image processing challenging. Recent algorithms based on deep neural networks, as advanced as they are, are commonly trained and evaluated on datasets of high-fidelity images which are typically not captured from aerial views. In this work we evaluate a number of deep neural network based object detection algorithms in the context of aerial search and rescue scenarios where real-time and robust detection of human bodies is a priority. We provide an evaluation using a number of video sequences collected in-flight using Unmanned Aerial Vehicle (UAV) platforms in different environmental conditions. We also describe the detection performance degradation under limited bitrate compression using H.264, H.265 and VP9 video codecs, in addition to analyzing the timing effects of moving image processing tasks to off-board entities.

[626] Andrzej Szalas. 2019.
Decision-Making Support Using Nonmonotonic Probabilistic Reasoning.
In Czarnowski I., Howlett R., Jain L., editors, Intelligent Decision Technologies 2019, pages 39–51. In series: Smart Innovation, Systems and Technologies #142. Springer.
DOI: 10.1007/978-981-13-8311-3_4.

[625] Lukasz Bialek, Barbara Dunin-Keplicz and Andrzej Szalas. 2019.
Belief Shadowing.
In Weyns D., Mascardi V., Ricci A., editors, Engineering Multi-Agent Systems. EMAS 2018, pages 158–180. In series: Lecture Notes in Computer Science #11375. Springer.
DOI: 10.1007/978-3-030-25693-7_9.

[624] Barbara Dunin-Keplicz, Inga RŁb and Andrzej Szalas. 2019.
Doxastic Group Reasoning via Multiple Belief Shadowing.
In Baldoni M., Dastani M., Liao B., Sakurai Y., Zalila Wenkstern R., editors, PRIMA 2019: Principles and Practice of Multi-Agent Systems, pages 271–288. In series: Lecture Notes in Computer Science #11873. Springer. ISBN: 978-3-030-33792-6, 978-3-030-33791-9.
DOI: 10.1007/978-3-030-33792-6_17.
Note: Funding agencies:  Polish National Science Centre [2015/19/B/ST6/02589]; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research FSR (SymbiKBot Project)

[623] Full text  David BergstrŲm, Mattias Tiger and Fredrik Heintz. 2019.
Bayesian optimization for selecting training and validation data for supervised machine learning.
In 31st annual workshop†of the†Swedish Artificial Intelligence Society†(SAIS 2019), UmeŚ, Sweden, June 18-19, 2019..

Validation and verification of supervised machine learning models is becoming increasingly important as their complexity and range of applications grows. This paper describes an extension to Bayesian optimization which allows for selecting both training and validation data, in cases where data can be generated or calculated as a function of a spatial location.

[622] Anton Silfver. 2019.
Short-Term Forecasting of Taxi Demand using a two Channelled Convolutional LSTM network.
Student Thesis. 39 pages. ISRN: LIU-IDA/LITH-A--19/097‚ÄĒSE.

In this thesis a model capable of predicting taxidemand with high accuracy across five different real world single company datasets is presented. The model uses historical drop off and arrival information to make accurate shortterm predictions about future taxi demand. The model is compared to and outperforms both LSTM and statistical baselines. This thesis uniquely uses a different tessellation strategy which makes the results directly applicable to smaller taxi companies.This paper shows that accurate short term predictions of taxi demand can be made using real world data available to taxi companies. MSE is also shown to be a more robust to uneven demand distributions across cities than MAE. Adding drop offs to the input had provided only marginal improvements in the performance of the model.

[621] Christoffer Fors Johansson. 2019.
Arrival Time Predictions for Buses using Recurrent Neural Networks.
Student Thesis. 65 pages. ISRN: LIU-IDA/LITH-EX-A--19/098--SE.

In this thesis, two different types of bus passengers are identified. These two types, namely current passengers and passengers-to-be have different needs in terms of arrival time predictions. A set of machine learning models based on recurrent neural networks and long short-term memory units were developed to meet these needs. Furthermore, bus data from the public transport in √Ėsterg√∂tland county, Sweden, were collected and used for training new machine learning models. These new models are compared with the current prediction system that is used today to provide passengers with arrival time information.The models proposed in this thesis uses a sequence of time steps as input and the observed arrival time as output. Each input time step contains information about the current state such as the time of arrival, the departure time from thevery first stop and the current position in Cartesian coordinates. The targeted value for each input is the arrival time at the next time step. To predict the rest of the trip, the prediction for the next step is simply used as input in the next time step.The result shows that the proposed models can improve the mean absolute error per stop between 7.2% to 40.9% compared to the system used today on all eight routes tested. Furthermore, the choice of loss function introduces models thatcan meet the identified passengers need by trading average prediction accuracy for a certainty that predictions do not overestimate or underestimate the target time in approximately 95% of the cases.

[620] Olov Andersson and Patrick Doherty. 2019.
Deep RL for Autonomous Robots: Limitations and Safety Challenges.
In , pages 489–495. ESANN. ISBN: 9782875870650.

With the rise of deep reinforcement learning, there has also been a string of successes on continuous control problems using physics simulators. This has lead to some optimism regarding use in autonomous robots and vehicles. However, to successful apply such techniques to the real world requires a firm grasp of their limitations. As recent work has raised questions of how diverse these simulation benchmarks really are, we here instead analyze a popular deep RL approach on toy examples from robot obstacle avoidance. We find that these converge very slowly, if at all, to safe policies. We identify convergence issues on stochastic environments and local minima as problems that warrant more attention for safety-critical control applications.

[619] Magnus Selin. 2019.
Efficient Autonomous Exploration Planning of Large-Scale 3D-Environments: A tool for autonomous 3D exploration indoor.
Student Thesis. 50 pages. ISRN: LIU-IDA/LITH-EX-A--19/017--SE.

Exploration is of interest for autonomous mapping and rescue applications using unmanned vehicles. The objective is to, without any prior information, explore all initially unmapped space.We present a system that can perform fast and efficient exploration of large scale arbitrary 3D environments. We combine frontier exploration planning (FEP) as a global planning strategy, together with receding horizon planning (RH-NBVP) for local planning. This leads to plans that incorporate information gain along the way, but do not get stuck in already explored regions. Furthermore, we make the potential information gain estimation more efficient, through sparse ray-tracing, and caching of already estimated gains. The worked carried out in this thesis has been published as a paper in Robotand Automation letters and presented at the International Conference on Robotics and Automation in Montreal 2019.

[618] Viktor Holmgren. 2019.
General-purpose maintenance planning using deep reinforcement learning and Monte Carlo tree search.
Student Thesis. 42 pages. ISRN: LIU-IDA/LITH-EX-A--19/096--SE.

Maintenance planning and execution is increasingly important for the modern industrial sector. Maintenance costs can amount to a major part of industrial spending. However, it is not as simple as just reducing maintenance budgets. A balance must be struck between risking unplanned downtime and the costs of maintenance efforts, in order to keep the profit margins needed to compete in the global markets of today. One approach to improve the effectiveness of industries is to apply intelligent maintenance planners. In this thesis, a general-purpose maintenance planner based on Monte-Carlotree search and deep reinforcement learning is presented. This planner was evaluated and compared against two different periodic planners as well as the oracle lower bound on four different maintenance scenarios. These four scenarios are all based on servicing wind turbines. All scenarios include imperfect maintenance actions, as well as uncertainty in terms of the outcomes of maintenance actions. Furthermore, the four scenarios include both single and multi-component variants. The evaluation showed that the proposed method is outperforming both periodic planners in three of the four scenarios, with the forth being inconclusive. These results indicate that the maintenance planner introduced in this paper is a viable method, at least for these types of maintenance problems. However, further research is needed on this topic of maintenance planning under uncertainty. More specifically, the viability of the proposed method on a more diverse set of maintenance problems is needed to draw any clear general conclusions. Finally, possible improvements to the training process that are discussed in this thesis should be investigated.

[617] Fredrik Bengtsson and Adam Combler. 2019.
Automatic Dispatching of Issues using Machine Learning.
Student Thesis. 90 pages. ISRN: LIU-IDA/LITH-EX-A--19/043--SE.

Many software companies use issue tracking systems to organize their work. However, when working on large projects, across multiple teams, a problem of finding the correctteam to solve a certain issue arises. One team might detect a problem, which must be solved by another team. This can take time from employees tasked with finding the correct team and automating the dispatching of these issues can have large benefits for the company. In this thesis, the use of machine learning methods, mainly convolutional neural networks (CNN) for text classification, has been applied to this problem. For natural language processing both word- and character-level representations are commonly used. The results in this thesis suggests that the CNN learns different information based on whether word- or character-level representation is used. Furthermore, it was concluded that the CNN models performed on similar levels as the classical Support Vector Machine for this task. When compared to a human expert, working with dispatching issues, the best CNN model performed on a similar level when given the same information. The high throughput of a computer model, therefore, suggests automation of this task is very much possible.

[616] Full text  Johan KšllstrŲm and Fredrik Heintz. 2019.
Reinforcement Learning for Computer Generated Forces using Open-Source Software.
In Proceedings of the 2019 Interservice/Industry Training, Simulation, and Education Conference (IITSEC), pages 1–11.
Conference Agenda: https://www.xcdsystem.com/iitsec/program...
Paper: https://s3.amazonaws.com/amz.xcdsystem.c...
I/ITSEC Knowledge Repository: http://www.iitsecdocs.com/volumes

The creation of behavior models for computer generated forces (CGF) is a challenging and time-consuming task, which often requires expertise in programming of complex artificial intelligence algorithms. This makes it difficult for a subject matter expert with knowledge about the application domain and the training goals to build relevant scenarios and keep the training system in pace with training needs. In recent years, machine learning has shown promise as a method for building advanced decision-making models for synthetic agents. Such agents have been able to beat human champions in complex games such as poker, Go and StarCraft. There is reason to believe that similar achievements are possible in the domain of military simulation. However, in order to efficiently apply these techniques, it is important to have access to the right tools, as well as knowledge about the capabilities and limitations of algorithms. This paper discusses efficient applications of deep reinforcement learning, a machine learning technique that allows synthetic agents to learn how to achieve their goals by interacting with their environment. We begin by giving an overview of available open-source frameworks for deep reinforcement learning, as well as libraries with reference implementations of state-of-the art algorithms. We then present an example of how these resources were used to build a reinforcement learning environment for a CGF software intended to support training of fighter pilots. Finally, based on our exploratory experiments in the presented environment, we discuss opportunities and challenges related to the application of reinforcement learning techniques in the domain of air combat training systems, with the aim to efficiently construct high quality behavior models for computer generated forces.

[615] Sebastian Sibelius Parmbšck. 2019.
HMMs and LSTMs for On-line Gesture Recognition on the Stylaero Board: Evaluating and Comparing Two Methods.
Student Thesis. 36 pages. ISRN: LIU-IDA/LITH-EX-A--2019/091--SE.

In this thesis, methods of implementing an online gesture recognition system for the novel Stylaero Board device are investigated. Two methods are evaluated - one based on LSTMs and one based on HMMs - on three kinds of gestures: Tap, circle, and flick motions. A method’s performance was measured in its accuracy in determining both whether any of the above listed gestures were performed and, if so, which gesture, in an online single-pass scenario. Insight was acquired regarding the technical challenges and possible solutions to the online aspect of the problem. Poor performance was, however, observed in both methods, with a likely culprit identified as low quality of training data, due to an arduous and complex gesture performance capturing process. Further research improving on the process of gathering data is suggested.

[614] Full text  Johan KšllstrŲm and Fredrik Heintz. 2019.
Multi-Agent Multi-Objective Deep Reinforcement Learning for Efficient and Effective Pilot Training.
In Ingo Staack and Petter Krus, editors, Proceedings of the 10th Aerospace Technology Congress (FT), pages 101–111. In series: LinkŲping Electronic Conference Proceedings #162. ISBN: 978-91-7519-006-8.
DOI: 10.3384/ecp19162011.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

The tactical systems and operational environment of modern fighter aircraft are becoming increasingly complex. Creating a realistic and relevant environment for pilot training using only live aircraft is difficult, impractical and highly expensive. The Live, Virtual and Constructive (LVC) simulation paradigm aims to address this challenge. LVC simulation means linking real aircraft, ground-based systems and soldiers (Live), manned simulators (Virtual) and computer controlled synthetic entities (Constructive). Constructive simulation enables realization of complex scenarios with a large number of autonomous friendly, hostile and neutral entities, which interact with each other as well as manned simulators and real systems. This reduces the need for personnel to act as role-players through operation of e.g. live or virtual aircraft, thus lowering the cost of training. Constructive simulation also makes it possible to improve the availability of training by embedding simulation capabilities in live aircraft, making it possible to train anywhere, anytime. In this paper we discuss how machine learning techniques can be used to automate the process of constructing advanced, adaptive behavior models for constructive simulations, to improve the autonomy of future training systems. We conduct a number of initial experiments, and show that reinforcement learning, in particular multi-agent and multi-objective deep reinforcement learning, allows synthetic pilots to learn to cooperate and prioritize among conflicting objectives in air combat scenarios. Though the results are promising, we conclude that further algorithm development is necessary to fully master the complex domain of air combat simulation.

[613] Full text  Daniel de Leng. 2019.
Robust Stream Reasoning Under Uncertainty.
PhD Thesis. In series: LinkŲping Studies in Science and Technology. Dissertations #2006. LinkŲping University Electronic Press. 207 pages. ISBN: 9789176850138.
DOI: 10.3384/diss.diva-157633.
Fulltext: https://doi.org/10.3384/diss.diva-157633
preview image: http://liu.diva-portal.org/smash/get/div...

Vast amounts of data are continually being generated by a wide variety of data producers. This data ranges from quantitative sensor observations produced by robot systems to complex unstructured human-generated texts on social media. With data being so abundant, the ability to make sense of these streams of data through reasoning is of great importance. Reasoning over streams is particularly relevant for autonomous robotic systems that operate in physical environments. They commonly observe this environment through incremental observations, gradually refining information about their surroundings. This makes robust management of streaming data and their refinement an important problem.Many contemporary approaches to stream reasoning focus on the issue of querying data streams in order to generate higher-level information by relying on well-known database approaches. Other approaches apply logic-based reasoning techniques, which rarely consider the provenance of their symbolic interpretations. In this work, we integrate techniques for logic-based stream reasoning with the adaptive generation of the state streams needed to do the reasoning over. This combination deals with both the challenge of reasoning over uncertain streaming data and the problem of robustly managing streaming data and their refinement.The main contributions of this work are (1) a logic-based temporal reasoning technique based on path checking under uncertainty that combines temporal reasoning with qualitative spatial reasoning; (2) an adaptive reconfiguration procedure for generating and maintaining a data stream required to perform spatio-temporal stream reasoning over; and (3) integration of these two techniques into a stream reasoning framework. The proposed spatio-temporal stream reasoning technique is able to reason with intertemporal spatial relations by leveraging landmarks. Adaptive state stream generation allows the framework to adapt to situations in which the set of available streaming resources changes. Management of streaming resources is formalised in the DyKnow model, which introduces a configuration life-cycle to adaptively generate state streams. The DyKnow-ROS stream reasoning framework is a concrete realisation of this model that extends the Robot Operating System (ROS). DyKnow-ROS has been deployed on the SoftBank Robotics NAO platform to demonstrate the system's capabilities in a case study on run-time adaptive reconfiguration. The results show that the proposed system - by combining reasoning over and reasoning about streams - can robustly perform stream reasoning, even when the availability of streaming resources changes.

[612] Filip StrŲmbšck, Linda Mannila, Mikael Asplund and Mariam Kamkar. 2019.
A Student's View of Concurrency: A Study of Common Mistakes in Introductory Courses on Concurrency.
In Proceedings of the 2019 ACM Conference on International Computing Education Research, pages 229–237. Association for Computing Machinery (ACM). ISBN: 978-1-4503-6185-9.
DOI: 10.1145/3291279.3339415.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

This paper investigates common misconceptions held by students regarding concurrency in order to better understand how concurrency education can be improved in the future. As a part of the exam in two courses on concurrency and operating systems, students were asked to identify and eliminate any concurrency issues in a piece of code as a part of their final exam. Different types of mistakes were identified and the 216 answers were sorted into categories accordingly. The results presented in this paper show that while most students were able to identify the cause of an issue given its symptoms, only approximately half manage to successfully eliminate the concurrency issues. Many of the incorrect solutions fail to associate shared data with a synchronization primitive, e.g. using one lock to protect multiple instances of a data structure, or multiple locks to protect the same instance in different situations. This suggests that students may not only have trouble dealing with concepts related to concurrency, but also more fundamental concepts related to the underlying computational model. Finally, this paper proposes possible explanations for the students' mistakes in terms of improper mental models, and suggests types of problems that highlight the issues with these mental models to improve students' understanding of the subject.

[611] Full text  Johan KšllstrŲm and Fredrik Heintz. 2019.
Tunable Dynamics in Agent-Based Simulation using Multi-Objective Reinforcement Learning.
In Proceedings of the 2019 Adaptive and Learning Agents Workshop (ALA), 2019, pages 1–7.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Agent-based simulation is a powerful tool for studying complex systems of interacting agents. To achieve good results, the behavior models used for the agents must be of high quality. Traditionally these models have been handcrafted by domain experts. This is a difficult, expensive and time consuming process. In contrast, reinforcement learning allows agents to learn how to achieve their goals by interacting with the environment. However, after training the behavior of such agents is often static, i.e. it can no longer be affected by a human. This makes it difficult to adapt agent behavior to specific user needs, which may vary among different runs of the simulation. In this paper we address this problem by studying how multi-objective reinforcement learning can be used as a framework for building tunable agents, whose characteristics can be adjusted at runtime to promote adaptiveness and diversity in agent-based simulation. We propose an agent architecture that allows us to adapt popular deep reinforcement learning algorithms to multi-objective environments. We empirically show that our method allows us to train tunable agents that can approximate the policies of multiple species of agents.

[610] Lukasz Bialek, Barbara Dunin-Keplicz and Andrzej Szalas. 2019.
A paraconsistent approach to actions in informationally complex environments.
Annals of Mathematics and Artificial Intelligence, 86(4):231–255. SPRINGER.
DOI: 10.1007/s10472-019-09627-9.
Note: Funding Agencies|Polish National Science Centre [2015/19/B/ST6/02589]; ELLIIT Network Organization for Information and Communication Technology; Swedish Foundation for Strategic Research FSR (SymbiKBot Project)
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Contemporary systems situated in real-world open environments frequently have to cope with incomplete and inconsistent information that typically increases complexity of reasoning and decision processes. Realistic modeling of such informationally complex environments calls for nuanced tools. In particular, incomplete and inconsistent information should neither trivialize nor stop both reasoning or planning. The paper introduces ACTLOG, a rule-based four-valued language designed to specify actions in a paraconsistent and paracomplete manner. ACTLOG is an extension of 4QL(Bel), a language for reasoning with paraconsistent belief bases. Each belief base stores multiple world representations. In this context, ACTLOGs action may be seen as a belief bases transformer. In contrast to other approaches, ACTLOG actions can be executed even when the underlying belief base contents is inconsistent and/or partial. ACTLOG provides a nuanced action specification tools, allowing for subtle interplay among various forms of nonmonotonic, paraconsistent, paracomplete and doxastic reasoning methods applicable in informationally complex environments. Despite its rich modeling possibilities, it remains tractable. ACTLOG permits for composite actions by using sequential and parallel compositions as well as conditional specifications. The framework is illustrated on a decontamination case study known from the literature.

[609] Richard Wigren and Filip Cornell. 2019.
Marketing Mix Modelling: A comparative study of statistical models.
Student Thesis. 113 pages. ISRN: LIU-IDA/LITH-EX-A--19/054--SE.

Deciding the optimal media advertisement spending is a complex issue that many companies today are facing. With the rise of new ways to market products, the choices can appear infinite. One methodical way to do this is to use Marketing Mix Modelling (MMM), in which statistical modelling is used to attribute sales to media spendings. However, many problems arise during the modelling. Modelling and mitigation of uncertainty, time-dependencies of sales, incorporation of expert information and interpretation of models are all issues that need to be addressed. This thesis aims to investigate the effectiveness of eight different statistical and machine learning methods in terms of prediction accuracy and certainty, each one addressing one of the previously mentioned issues. It is concluded that while Shapley Value Regression has the highest certainty in terms of coefficient estimation, it sacrifices some prediction accuracy. The overall highest performing model is the Bayesian hierarchical model, achieving both high prediction accuracy and high certainty.

[608] David Hilm and David Rahim. 2019.
Two-factor Authentication and Digital Signing for an Enterprise System utilizing Yubikey.
Student Thesis. 10 pages. ISRN: LIU-IDA/LITH-EX-G--19/040--SE.

The use of a second factor to increase the security of systems is growing and has continued to do so for a long time. This thesis explores options for implementation to use a YubiKey as an authentication method (OTP) as well as for signing digital transactions through a web browser client. Measures of network overhead that occurs in conjunction with Digital Signing of transactions are also disclosed. Our findings show that YubiKey provides flexible and readily available solutions that can be used with only small implementations for OTP authentication. It is also shown that the major concern for implementing a solution for a web browser is to intuitively use certificates stored on a USB-device without installing any plugins or with the use of a third-party application running on the client machine.

[607] Martin Lundberg. 2019.
Automatic parameter tuning in localization algorithms.
Student Thesis. 57 pages. ISRN: LIU-IDA/LITH-EX-A--19/052--SE.

Many algorithms today require a number of parameters to be set in order to perform well in a given application. The tuning of these parameters is often difficult and tedious to do manually, especially when the number of parameters is large. It is also unlikely that a human can find the best possible solution for difficult problems. To be able to automatically find good sets of parameters could both provide better results and save a lot of time.The prominent methods Bayesian optimization and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) are evaluated for automatic parameter tuning in localization algorithms in this work. Both methods are evaluated using a localization algorithm on different datasets and compared in terms of computational time and the precision and recall of the final solutions. This study shows that it is feasible to automatically tune the parameters of localization algorithms using the evaluated methods. In all experiments performed in this work, Bayesian optimization was shown to make the biggest improvements early in the optimization but CMA-ES always passed it and proceeded to reach the best final solutions after some time. This study also shows that automatic parameter tuning is feasible even when using noisy real-world data collected from 3D cameras.

[606] Jacek Szklarski, Lukasz Bialek and Andrzej Szalas. 2019.
Paraconsistent Reasoning in Cops and Robber Game with Uncertain Information: A Simulation-Based Analysis.
International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 27(3):429–455. WORLD SCIENTIFIC PUBL CO PTE LTD.
DOI: 10.1142/S021848851950020X.
Note: Funding Agencies|Polish National Science Centre [2012/05/B/ST6/03094, 2015/19/B/ST6/02589]

We apply a non-classical four-valued logic in the process of reasoning regarding strategies for cops in a modified game of \"Cops and Robber\" played on a graph. We extend the game by introducing uncertainty in a form of random failures of detecting devices. This is realized by allowing that a robber can be detected in a node only with the given probability P-A. Additionally, with the probability P-F, cops can be given a false-positive, i.e., they are informed that the robber is located at some node, whereas it is located somewhere else. Consequently, non-zero P-F introduces a measurement noise into the system. All the cops have access to information provided by the detectors and can communicate with each other, so they can coordinate the search. By adjusting the number of detectors,P-A, and P-F we can achieve a smooth transition between the two well-known variants of the game: \"with fully visible robber\" and \"with invisible robber\". We compare a simple probabilistic strategy for cops with the non-parametric strategy based on reasoning with a four-valued paraconsistent logic. It is shown that this novel approach leads to a good performance, as measured by the required mean catch-time. We conclude that this type of reasoning can be applied in real-world applications where there is no knowledge about the underlying source of errors which is particularly useful in robotics.

[605] Elina Lundberg and Erica Gavefalk. 2019.
Investigating the impact on subjective satisfaction and learnability when adopting cloud in an SME.
Student Thesis. 74 pages. ISRN: LIU-IDA/LITH-EX-A--19/030--SE.

Cloud services and solutions have served as a shift in the computer industry and create new opportunities for users. Clouds have been described as easily usable and fluid in terms of expansion and contraction depending on the real-time needs. Although the cloud is promoted with several benefits, it is not always apparent for the users that this is the case. Understanding both the benefits and challenges that exist is substantial for a successful adoption to cloud. This master’s thesis is conducted in collaboration with Exsitec ABand aims to investigate how the adoption of the cloud service Microsoft Azure will affect the development process. Also, it aims to provide a best practice for potentially needed updated working procedures, in terms of satisfaction and learnability. The investigation was performed through interviews and the System Usability Scale, to assess how the end users experienced development in a cloud environment. The thesis revealed that the Azure portal has low overall usability, but that there also exists an inconsistency of that perception. Two major factors that contributed to the satisfaction and learnability was the lack of documentation and that the Azure portal was considered hard to master. The SUS score revealed that the mean value was below an acceptable level, and thus changes in the company’s working procedures need to be implemented. Internal documentation regarding how the company should use both cloud in general, as well as the portal in particular, are required in order to increase the learnability and subjective satisfaction.

[604] Full text  David BergstrŲm. 2019.
Bayesian optimization for selecting training and validation data for supervised machine learning: using Gaussian processes both to learn the relationship between sets of training data and model performance, and to estimate model performance over the entire problem domain.
Student Thesis. 39 pages. ISRN: LIU-IDA/LITH-EX-A--19/016--SE.

Validation and verification in machine learning is an open problem which becomes increasingly important as its applications becomes more critical. Amongst the applications are autonomous vehicles and medical diagnostics. These systems all needs to be validated before being put into use or else the consequences might be fatal.This master’s thesis focuses on improving both learning and validating machine learning models in cases where data can either be generated or collected based on a chosen position. This can for example be taking and labeling photos at the position or running some simulation which generates data from the chosen positions.The approach is twofold. The first part concerns modeling the relationship between any fixed-size set of positions and some real valued performance measure. The second part involves calculating such a performance measure by estimating the performance over a region of positions.The result is two different algorithms, both variations of Bayesian optimization. The first algorithm models the relationship between a set of points and some performance measure while also optimizing the function and thus finding the set of points which yields the highest performance. The second algorithm uses Bayesian optimization to approximate the integral of performance over the region of interest. The resulting algorithms are validated in two different simulated environments.The resulting algorithms are applicable not only to machine learning but can also be used to optimize any function which takes a set of positions and returns a value, but are more suitable when the function is expensive to evaluate.

[603] Daniele DellAglio, Thomas Eiter, Fredrik Heintz and Danh Le-Phuoc. 2019.
Special issue on stream reasoning.
Semantic Web, 10(3):453–455. IOS PRESS.
DOI: 10.3233/SW-190351.

n/a

[602] Pernilla Eilert. 2019.
Learning behaviour trees for simulated fighter pilots in airborne reconnaissance missions: A grammatical evolution approach.
Student Thesis. 94 pages. ISRN: LIU-IDA/LITH-EX-A--19/015--SE.

Fighter pilots often find themselves in situations where they need to make quick decisions. Therefore an intelligent decision support system that suggests how the fighter pilot should act in a specific situation is vital. The aim of this project is to investigate and evaluate grammatical evolution paired with behaviour trees to develop a decision support system. This support system should control a simulated fighter pilot during an airborne reconnaissance mission. This thesis evaluates the complexity of the evolved trees and the performance, and robustness of the algorithm. Key factors were identified for a successful system: scenario, fitness function, initialisation technique and control parameters. The used techniques were decided based on increasing performance of the algorithm and decreasing complexity of the tree structures. The initialisation technique, the genetic operators and the selection functions performed well but the fitness function needed more work. Most of the experiments resulted in local maxima. A desired solution could only be found if the initial population contained an individual with a BT succeeding the mission. However, the implementation behaved as expected. More and longer simulations are needed to draw a conclusion of the performance based on robustness, when testing the evolved BT:s on different scenarios. Several methods were studied to decrease the complexity of the trees and the experiments showed a promising variation of complexity through the generations when the best fitness was fixed. A feature was added to the algorithm, to promote lower complexity when equal fitness value. The results were poor and implied that pruning would be a better fit after the simulations. Nevertheless, this thesis suggests that it is suitable to implement a decision support system based on grammatical evolution paired with behaviour trees as framework.

[601] Full text  Magnus Selin, Mattias Tiger, Daniel Duberg, Fredrik Heintz and Patric Jensfelt. 2019.
Efficient Autonomous Exploration Planning of Large Scale 3D-Environments.
IEEE Robotics and Automation Letters, 4(2):1699–1706. Institute of Electrical and Electronics Engineers (IEEE).
DOI: 10.1109/LRA.2019.2897343.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Exploration is an important aspect of robotics, whether it is for mapping, rescue missions or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this work we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries.

[600] Full text  Daniel de Leng and Fredrik Heintz. 2019.
Approximate Stream Reasoning with Metric Temporal Logic under Uncertainty.
In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), pages 2760–2767. AAAI Press.
AAAI Digital Library Conferences: https://aaai.org/Library/conferences-lib...

Stream reasoning can be defined as incremental reasoning over incrementally-available information. The formula progression procedure for Metric Temporal Logic (MTL) makes use of syntactic formula rewritings to incrementally evaluate formulas against incrementally-available states. Progression however assumes complete state information, which can be problematic when not all state information is available or can be observed, such as in qualitative spatial reasoning tasks or in robotics applications. In those cases, there may be uncertainty as to which state out of a set of possible states represents the ‚Äėtrue‚Äô state. The main contribution of this paper is therefore an extension of the progression procedure that efficiently keeps track of all consistent hypotheses. The resulting procedure is flexible, allowing a trade-off between faster but approximate and slower but precise progression under uncertainty. The proposed approach is empirically evaluated by considering the time and space requirements, as well as the impact of permitting varying degrees of uncertainty.

2018
[599] Fredrik LŲfgren, Sofia Thunberg and Sam Thellman. 2018.
LetterMoose: A Handwriting Tutor Robot.
In .

We present a simple robotic tutor designed to help raise handwriting competency in school-aged children. \"LetterMoose\" shows the steps in how a letter is formed by writing on regular piece of paper. The child is invited to imitate LetterMoose and to scan its own letters using LetterMoose in order to get evaluative feedback (both qualitative and quantitative). We propose that LetterMoose might be particularly useful for helping children with autism attain handwriting competency, as children in this group are more likely to suffer from writing difficulties and may uniquely benefit from interacting with robot technology.

[598] Full text  Daniel de Leng and Fredrik Heintz. 2018.
Partial-State Progression for Stream Reasoning with Metric Temporal Logic.
In SIXTEENTH INTERNATIONAL CONFERENCE ON PRINCIPLES OF KNOWLEDGE REPRESENTATION AND REASONING, pages 633–634. ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
Note: Funding Agencies|National Graduate School in Computer Science, Sweden (CUGS)

The formula progression procedure for Metric Temporal Logic (MTL), originally proposed by Bacchus and Kabanza, makes use of syntactic formula rewritings to incrementally evaluate MTL formulas against incrementally-available states. Progression however assumes complete state information, which can be problematic when not all state information is available or can be observed, such as in qualitative spatial reasoning tasks or in robot applications. Our main contribution is an extension of the progression procedure to handle partial state information. For each missing truth value, we efficiently consider all consistent hypotheses by branching progression for each such hypothesis. The resulting procedure is flexible, allowing a trade-off between faster but approximate and slower but precise partial-state progression.

[597] Mariusz Wzorek, Cyrille Berger, Piotr Rudol and Patrick Doherty. 2018.
Deployment of Ad Hoc Network Nodes Using UAVs for Search and Rescue Missions.
In 2018 6TH INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON). In series: International Electrical Engineering Congress #??. IEEE. ISBN: 978-1-5386-2317-6.
DOI: 10.1109/IEECON.2018.8712230.
Note: Funding Agencies|Swedish Research Council CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research [RIT 15-0097]

Due to the maturity of technological development, widespread use of Unmanned Aerial Vehicles (UAVs) is becoming prevalent in the civil and commercial sectors. One promising area of application is in emergency rescue support. As recently seen in a number of natural catastrophes such as the hurricanes in Texas, Florida and Puerto Rico, major communication and electrical infrastructure is knocked out, leading to an inability to communicate between the victims and rescuers on the ground as well as between rescuers themselves. This paper studies the feasibility of using heterogeneous teams of UAVs to rapidly deliver and establish ad hoc communication networks in operational environments through autonomous in-air delivery of CommKits that serve as nodes in local ad hoc networks. Hardware and software infrastructures for autonomous CommKit delivery in addition to CommKit specification and construction is considered. The results of initial evaluation of two design alternatives for CommKits are presented based on more than 25 real flight tests in different weather conditions using a commercial small-scale UAV platform.

[596] Tom Ziemke, Mattias Arvola, Nils Dahlbšck and Erik Billing. 2018.
Proceedings of the 14th SweCog Conference: LinkŲping 2018, 11-12 October.
Conference Proceedings. In series: SkŲvde University Studies in Informatics #2018:1. University of SkŲvde. 30 pages. ISBN: 9789198366730.

Welcome to SweCog 2018 in Linköping!This booklet contains the program and short papers for oral and poster presentations at SweCog 2018, this year’s edition of the annual conference of the Swedish Cognitive Science Society. Following the SweCog tradition and its aim to support networking among researchers in cognitive science and related areas, contributions cover a wide spectrum of research.A trend in recent years, also reflected in this year’s conference program, is an increasing number of contributions that deal with different types of autonomous technologies, such as social robots, virtual agents or automated vehicles, and in particular people’s interaction with such systems. This clearly is a growing research area of high societal relevance, where cognitive science - with its interdisciplinary and human-centered approach - can make significant contributions.We look forward to two exciting days in Linköping, and we thank the many people who have contributed to the organization of this year’s SweCog conference, in particular of course all authors and reviewers! The organization of SweCog 2018 has been supported by the Faculty of Arts and Sciences, the Department of Culture Communication (IKK), and the Department of Computer Information Science (IDA) at Linköpping University, as well as Cambio Healthcare Systems and Visual Sweden.Tom Ziemke, Mattias Arvola, Nils Dahlbäc and Erik Billing

[595] Veronika Petrovych, Sam Thellman and Tom Ziemke. 2018.
Human Interpretation of Goal-Directed Autonomous Car Behavior.
In COGSCI2018 Changing / minds, 40th annual cognitive science society meeting, Madison, Wisconsin, USA, July 25-28, pages 2235–2240. Cognitive Science Society. ISBN: 9780991196784.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

People increasingly interact with different types of autonomous robotic systems, ranging from humanoid social robots to driverless vehicles. But little is known about how people interpret the behavior of such systems, and in particular if and how they attribute cognitive capacities and mental states to them. In a study concerning people‚Äôs interpretations of autonomous car behavior, building on our previous research on human-robot interaction, participants were presented with (1) images of cars ‚Äď either with or without a driver ‚Äď exhibiting various goal-directed traffic behaviors, and (2) brief verbal descriptions of that behavior. They were asked to rate the extent to which these behaviors were intentional and judge the plausibility of different types of causal explanations. The results indicate that people (a) view autonomous car behavior as goal-directed, (b) discriminate between intentional and unintentional autonomous car behaviors, and (c) view the causes of autonomous and human traffic behaviors similarly, in terms of both intentionality ascriptions and behavior explanations. However, there was considerably lower agreement in participant ratings of the driverless behaviors, which might indicate an increased difficulty in interpreting goal-directed behavior of autonomous systems.

[594] Anton HŲlscher. 2018.
A Cycle-Trade Heuristic for the Weighted k-Chinese Postman Problem.
Student Thesis. 23 pages. ISRN: LIU-IDA/LITH-EX-G--18/073--SE.

This study aims to answer whether a heuristic that trades cycles between the tours in a solution would show good results when trying to solve the Weighted k-Chinese Postman Problem for undirected graphs, of varying size, representing neighbourhoods in Sweden.A tabu search heuristic was implemented with each iteration consisting of giving a cycle from the most expensive tour to the cheapest. The heuristic performed increasingly well for graphs of increasing size, although the solution quality decreased when increasing the number of tours to be used in the solution. It is suspected that the cause for this behavior is due to the heuristic only giving cycles from the most expensive tour, not considering trading cycles from other tours in the solution. It is believed that a heuristic considering more than only the most expensive tour when trading cycles would produce even better solutions.

[593] Francesco Luca De Angelis, Giovanna Di Marzo Serugendo and Andrzej Szalas. 2018.
Paraconsistent Rule-Based Reasoning with Graded Truth Values.
, 5(1):185–220. College Publications.
Link: http://www.collegepublications.co.uk/dow...

Modern artificial systems, such as cooperative traffic systems or swarm robotics, are made of multiple autonomous agents, each handling uncertain, partial and potentially inconsistent information, used in their reasoning and decision making. Graded reasoning, being a suitable tool for addressing phenomena related to such circumstances, is investigated in the literature in many contexts ‚Äď from graded modal logics to various forms of approximate reasoning. In this paper we first introduce a family of many-valued paraconsistent logics parametrised by a number of truth/falsity/inconsistency grades allowing one to handle multiple truth-values at the desired level of accuracy. Second, we define a corresponding family of rule-based languages with graded truth-values as first-class citizens, enjoying tractable query evaluation. In addition, we introduce introspection operators allowing one to resolve inconsistencies and/or lack of information in a non-monotonic manner. We illustrate and discuss the use of the framework in an autonomous robot scenario.

[592] Barbara Dunin-K?plicz, Alina Powala (Strachocka) and Andrzej Szalas. 2018.
Variations on Ja?kowski?s Discursive Logic.
In √Āngel GarridoUrszula Wybraniec-Skardowska, editor, The Lvov-Warsaw School. Past and Present, pages 485–497. In series: Studies in Universal Logic #??. Birkhšuser. ISBN: 9783319654294, 9783319654300.
DOI: 10.1007/978-3-319-65430-0_34.

StanisŇāaw JaŇõkowski, in his 1948‚Äď1949 papers on propositional calculus for contradictory deductive systems, proposed discursive logic D<sub>2</sub>. The main motivation behind D<sub>2</sub> is the need to properly deal with contradictions that naturally appear in many areas of philosophy and discourse. The intuitive justification of this logic reflects knowledge fusion occurring when ‚Äúthe theses advanced by several participants in a discourse are combined into a single system.‚ÄĚ This point of view was seminal in the mid twentieth century and remains visionary nowadays.In contemporary autonomous systems operating in dynamic, unpredictable information-rich environments, distributed reasoning routinely takes place. This explains the key role of knowledge fusion, among others, in Distributed Artificial Intelligence. Therefore, different types of modern knowledge and belief bases become primarily concerned with inconsistent or lacking information. This requirement leads to recent approaches to paraconsistent and paracomplete reasoning, where nonmonotonic techniques for disambiguating inconsistencies and completing missing knowledge can be applied.In this chapter we remind JaŇõkowski‚Äôs seminal, pioneering work on paraconsistent reasoning and indicate some of its relations to contemporary research on reasoning in Distributed AI.

[591] Patrick Doherty and Andrzej Szalas. 2018.
Signed Dual Tableaux for Kleene Answer Set Programs.
In GoliŇĄska-Pilarek J., Zawidzki M., editors, Ewa Or?owska on Relational Methods in Logic and Computer Science, pages 233–252. In series: Outstanding Contributions to Logic #17. Springer. ISBN: 9783319978789, 9783319978796.
DOI: 10.1007/978-3-319-97879-6_9.

<em>Dual tableaux</em> were introduced by Rasiowa and Sikorski (1960) as a cut free deduction system for classical first-order logic. In the current paper, a sound and complete proof procedure based on dual tableaux is proposed for<em> R</em><sub><em>3</em> </sub>which is the standard Kleene logic augmented with a weak negation connective and an implication connective proposed, in another context, by Shepherdson (1989).<em> R<sub>3</sub></em>is used as a basis for defining Kleene Answer Set Programs (ASP<em><sup>K</sup></em>programs). The semantics forASP<em><sup>K</sup></em>programs is based on strongly supported models. Both entailment procedures and model generation procedures for normal and non-normalASP<em><sup>K</sup></em>programs are proposed based on the use of dual tableaux and a model filtering technique. The dual tableau proof procedure extended with a model filtering technique is shown to be sound and complete forASP<em><sup>K</sup></em>programs, both normal and non-normal. Since there is a direct relationship between answer sets for classical ASP programs and<em>R<sub>3</sub></em>models forASP<sup>K</sup>programs, it can be shown that the sound and complete dual tableaux proof procedure with filtering for ASPK\" role=\"presentation\"&gt;ASPKprograms is also sound and complete for classical normal ASP programs. For classical non-normal ASP programs, the proof procedure is only sound, since an alternative semantics for disjunction is used inASP<sup>K </sup>

[590] Lukasz Bialek, Barbara Dunin-Keplicz and Andrzej Szalas. 2018.
Towards a Paraconsistent Approach to Actions in Distributed Information-Rich Environments.
In Mirjana Ivanovińá, Costin BńÉdicńÉ, J√ľrgen Dix, Zoran Jovanovińá, Michele Malgeri, MiloŇ° Savińá, editors, Intelligent Distributed Computing XI, pages 49–60. In series: Studies in Computational Intelligence #737. Springer. ISBN: 9783319663784, 9783319663791.
DOI: 10.1007/978-3-319-66379-1_5.

The paper introduces ActLog, a rule-based language capable of specifying actions paraconsistently. ActLog is an extension of 4QL&amp;#xA0;Bel&amp;#xA0;\" role=\"presentation\"&gt; Bel , a rule-based language for reasoning with paraconsistent and paracomplete belief bases and belief structures. Actions considered in the paper act on belief bases rather than states represented as sets of ground literals. Each belief base stores multiple world representations which can be though of as a representation of possible states. In this context ActLog’s action may be then seen as a method of transforming one belief base into another. In contrast to other approaches, ActLog permits to execute actions even if the underlying belief base state is partial or inconsistent. Finally, the framework introduced in this paper is tractable.

[589] Linus Kortesalmi. 2018.
Gaussian Process Regression-based GPS Variance Estimation and Trajectory Forecasting.
Student Thesis. 59 pages. ISRN: LIU-IDA/LITH-EX-A--18/040--SE.

Spatio-temporal data is a commonly used source of information. Using machine learning to analyse this kind of data can lead to many interesting and useful insights. In this thesis project, a novel public transportation spatio-temporal dataset is explored and analysed. The dataset contains 282 GB of positional events, spanning two weeks of time, from all public transportation vehicles in √Ėsterg√∂tland county, Sweden. From the data exploration, three high-level problems are formulated: bus stop detection, GPS variance estimation, and arrival time prediction, also called trajectory forecasting. The bus stop detection problem is briefly discussed and solutions are proposed. Gaussian process regression is an effective method for solving regression problems. The GPS variance estimation problem is solved via the use of a mixture of Gaussian processes. A mixture of Gaussian processes is also used to predict the arrival time for public transportation buses. The arrival time prediction is from one bus stop to the next, not for the whole trajectory. The result from the arrival time prediction is a distribution of arrival times, which can easily be applied to determine the earliest and latest expected arrival to the next bus stop, alongside the most probable arrival time. The na√Įve arrival time prediction model implemented has a root mean square error of 5 to 19 seconds. In general, the absolute error of the prediction model decreases over time in each respective segment. The results from the GPS variance estimation problem is a model which can compare the variance for different environments along the route on a given trajectory.

[588] Erik Hansson. 2018.
Temporal Task and Motion Plans: Planning and Plan Repair: Repairing Temporal Task and Motion Plans Using Replanning with Temporal Macro Operators.
Student Thesis. 128 pages. ISRN: LIU-IDA/LITH-EX-A--18/047--SE.

This thesis presents an extension to the Temporal Fast Downward planning system that integrates motion planning in it and algorithms for generating two types of temporal macro operators expressible in PDDL2.1. The extension to the Temporal Fast Downward planning system includes, in addition to the integration of motion planning itself, an extension to the context-enhanced additive heuristic that uses information from the motion planning part to improve the heuristic estimate. The temporal macro operators expressible in PDDL2.1 are, to the author's knowledge, an area that is not studied within the context of plan repair before. Two types of temporal macro operators are presented along with algorithms for automatically constructing and using them when solving plan repair problems by replanning. Both the heuristic extension and the temporal macro operators were evaluated in the context of simulated unmanned aerial vehicles autonomously executing reconnaissance missions to identify targets and avoiding threats in unexplored areas. The heuristic extension was proved to be very helpful in the scenario. Unfortunately, the evaluation of the temporal macro operators indicated that the cost of introducing them is higher than the gain of using them for the scenario.

[587] Rasmus Johns Johns. 2018.
Intelligent Formation Control using Deep Reinforcement Learning.
Student Thesis. 53 pages. ISRN: LLIU-IDA/LITH-EX-A--2017/001--SE.

In this thesis, deep reinforcement learning is applied to the problem of formation control to enhance performance. The current state-of-the-art formation control algorithms are often not adaptive and require a high degree of expertise to tune. By introducing reinforcement learning in combination with a behavior-based formation control algorithm, simply tuning a reward function can change the entire dynamics of a group. In the experiments, a group of three agents moved to a goal which had its direct path blocked by obstacles. The degree of randomness in the environment varied: in some experiments, the obstacle positions and agent start positions were fixed between episodes, whereas in others they were completely random. The greatest improvements were seen in environments which did not change between episodes; in these experiments, agents could more than double their performance with regards to the reward. These results could be applicable to both simulated agents and physical agents operating in static areas, such as farms or warehouses. By adjusting the reward function, agents could improve the speed with which they approach a goal, obstacle avoidance, or a combination of the two. Two different and popular reinforcement algorithms were used in this work: Deep Double Q-Networks (DDQN) and Proximal Policy Optimization (PPO). Both algorithms showed similar success.

[586] Full text  Fredrik Pršntare and Fredrik Heintz. 2018.
An Anytime Algorithm for Simultaneous Coalition Structure Generation and Assignment.
In Tim Miller, Nir Oren, Yuko Sakurai, Itsuki Noda, Bastin Tony Roy Savarimuthu and Tran Cao Son, editors, PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings, pages 158–174. In series: Lecture Notes in Computer Science #11224. ISBN: 9783030030971, 9783030030988.
DOI: 10.1007/978-3-030-03098-8_10.

A fundamental problem in artificial intelligence is how to organize and coordinate agents to improve their performance and skills. In this paper, we consider simultaneously generating coalitions of agents and assigning the coalitions to independent tasks, and present an anytime algorithm for the simultaneous coalition structure generation and assignment problem. This optimization problem has many real-world applications, including forming goal-oriented teams of agents. To evaluate the algorithm’s performance, we extend established methods for synthetic problem set generation, and benchmark the algorithm against CPLEX using randomized data sets of varying distribution and complexity. We also apply the algorithm to solve the problem of assigning agents to regions in a major commercial strategy game, and show that the algorithm can be utilized in game-playing to coordinate smaller sets of agents in real-time.

[585] Full text  Olov Andersson, Oskar Ljungqvist, Mattias Tiger, Daniel Axehill and Fredrik Heintz. 2018.
Receding-Horizon Lattice-based Motion Planning with Dynamic Obstacle Avoidance.
In 2018 IEEE Conference on Decision and Control (CDC), pages 4467–4474. In series: Conference on Decision and Control (CDC) #2018. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781538613955, 9781538613948, 9781538613962.
DOI: 10.1109/CDC.2018.8618964.
Note: This work was partially supported by FFI/VINNOVA, the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) funded by Knut and Alice Wallenberg Foundation, the Swedish Foundation for Strategic Research (SSF) project Symbicloud, the ELLIIT Excellence Center at Linköping-Lund for Information Technology, Swedish Research Council (VR) Linnaeus Center CADICS, and the National Graduate School in Computer Science, Sweden (CUGS).
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

A key requirement of autonomous vehicles is the capability to safely navigate in their environment. However, outside of controlled environments, safe navigation is a very difficult problem. In particular, the real-world often contains both complex 3D structure, and dynamic obstacles such as people or other vehicles. Dynamic obstacles are particularly challenging, as a principled solution requires planning trajectories with regard to both vehicle dynamics, and the motion of the obstacles. Additionally, the real-time requirements imposed by obstacle motion, coupled with real-world computational limitations, make classical optimality and completeness guarantees difficult to satisfy. We present a unified optimization-based motion planning and control solution, that can navigate in the presence of both static and dynamic obstacles. By combining optimal and receding-horizon control, with temporal multi-resolution lattices, we can precompute optimal motion primitives, and allow real-time planning of physically-feasible trajectories in complex environments with dynamic obstacles. We demonstrate the framework by solving difficult indoor 3D quadcopter navigation scenarios, where it is necessary to plan in time. Including waiting on, and taking detours around, the motions of other people and quadcopters.

[584] Full text  Mikael Nilsson, Jonas KvarnstrŲm and Patrick Doherty. 2018.
Planning with Temporal Uncertainty, Resources and Non-Linear Control Parameters.
In Mathijs de Weerdt, Sven Koenig, Gabriele R√∂ger, Matthijs Spaan, editors, Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling (ICAPS), pages 180–189. In series: International Conference on Automated Planning and Scheduling #??. AAAI Press. ISBN: 978-1-57735-797-1.
AAAI Digital Library: http://www.aaai.org/Library/ICAPS/icaps1...

We consider a general and industrially motivated class of planning problems involving a combination of requirements that can be essential to autonomous robotic systems planning to act in the real world: Support for temporal uncertainty where nature determines the eventual duration of an action, resource consumption with a non-linear relationship to durations, and the need to select appropriate values for control parameters that affect time requirements and resource usage. To this end, an existing planner is extended with support for Simple Temporal Networks with Uncertainty, Timed Initial Literals, and temporal coverage goals. Control parameters are lifted from the main combinatorial planning problem into a constraint satisfaction problem that connects them to resource usage. Constraint processing is then integrated and interleaved with verification of temporal feasibility, using projections for partial temporal awareness in the constraint solver.

[583] Fredrik HŚkansson and Carl-Johan Larsson. 2018.
User-Based Predictive Caching of Streaming Media.
Student Thesis. 58 pages. ISRN: LIU-IDA/LITH-EX-A--18/033‚ÄĒSE.

Note: This thesis is written as a joint thesis between two students from different universities. This means the exact same thesis is published at two universities (LiU and KTH) but with different style templates. The other report has identification number: TRITA-EECS-EX-2018:403

Streaming media is a growing market all over the world which sets a strict requirement on mobile connectivity. The foundation for a good user experience when supplying a streaming media service on a mobile device is to ensure that the user can access the requested content. Due to the varying availability of mobile connectivity measures has to be taken to remove as much dependency as possible on the quality of the connection. This thesis investigates the use of a Long Short-Term Memory machine learning model for predicting a future geographical location for a mobile device. The predicted location in combination with information about cellular connectivity in the geographical area is used to schedule prefetching of media content in order to improve user experience and to reduce mobile data usage. The Long Short-Term Memory model suggested in this thesis achieves an accuracy of 85.15% averaged over 20000 routes and the predictive caching managed to retain user experience while decreasing the amount of data consumed.

[582] Alexander Kleiner. 2018.
The Low-Cost Evolution of AI in Domestic Floor Cleaning Robots.
The AI Magazine, 39(2):89–90. AMER ASSOC ARTIFICIAL INTELL.
DOI: 10.1609/aimag.v39i2.2806.

This article discusses AI methods deployed on domestic floor cleaning robots in the recent past and the way in which those methods are changing today. Formerly, innovations were tightly coupled with a price point customers were willing to pay. Today, there is a substantial increase in the AI found in these systems, driven by new challenges and scalable infrastructures.

[581] Full text  Mattias Tiger and Fredrik Heintz. 2018.
Gaussian Process Based Motion Pattern Recognition with Sequential Local Models.
In 2018 IEEE Intelligent Vehicles Symposium (IV), pages 1143–1149. In series: IEEE Intelligent Vehicles Symposium #2018. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781538644522, 9781538644515, 9781538644539.
DOI: 10.1109/IVS.2018.8500676.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Conventional trajectory-based vehicular traffic analysis approaches work well in simple environments such as a single crossing but they do not scale to more structurally complex environments such as networks of interconnected crossings (e.g. urban road networks). Local trajectory models are necessary to cope with the multi-modality of such structures, which in turn introduces new challenges. These larger and more complex environments increase the occurrences of non-consistent lack of motion and self-overlaps in observed trajectories which impose further challenges. In this paper we consider the problem of motion pattern recognition in the setting of sequential local motion pattern models. That is, classifying sub-trajectories from observed trajectories in accordance with which motion pattern that best explains it. We introduce a Gaussian process (GP) based modeling approach which outperforms the state-of-the-art GP based motion pattern approaches at this task. We investigate the impact of varying local model overlap and the length of the observed trajectory trace on the classification quality. We further show that introducing a pre-processing step filtering out stops from the training data significantly improves the classification performance. The approach is evaluated using real GPS position data from city buses driving in urban areas for extended periods of time.

[580] Adrian Sonnert. 2018.
Predicting inter-frequency measurements in an LTE network using supervised machine learning: a comparative study of learning algorithms and data processing techniques.
Student Thesis. 52 pages. ISRN: LIU-IDA/LITH-EX-A--18/017--SE.

With increasing demands on network reliability and speed, network suppliers need to effectivize their communications algorithms. Frequency measurements are a core part of mobile network communications, increasing their effectiveness would increase the effectiveness of many network processes such as handovers, load balancing, and carrier aggregation. This study examines the possibility of using supervised learning to predict the signal of inter-frequency measurements by investigating various learning algorithms and pre-processing techniques. We found that random forests have the highest predictive performance on this data set, at 90.7\% accuracy. In addition, we have shown that undersampling and varying the discriminator are effective techniques for increasing the performance on the positive class on frequencies where the negative class is prevalent. Finally, we present hybrid algorithms in which the learning algorithm for each model depends on attributes of the training data set. These algorithms perform at a much higher efficiency in terms of memory and run-time without heavily sacrificing predictive performance.

[579] GŲran Svensson and Jonas Westlund. 2018.
Intravenous bag monitoring with Convolutional Neural Networks.
Student Thesis. 12 pages. ISRN: LIU-IDA/LITH-EX-G--2018/048--SE.

Drip bags are used in hospital environments to administerdrugs and nutrition to patients. Ensuring that they are usedcorrectly and are refilled in time are important for the safetyof patients. This study examines the use of a ConvolutionalNeural Network (CNN) to monitor the fluid levels of drip bagsvia image recognition to potentially form the base of an earlywarning system, and assisting in making medical care moreefficient. Videos of drip bags were recorded as they wereemptying their contents in a controlled environment and fromdifferent angles. A CNN was built to analyze the recordeddata in order to predict a bags fluid level with a 5% intervalprecision from a given image. The results show that the CNNused performs poorly when monitoring fluid levels in dripbags.

[578] Full text  Daniel de Leng, Mattias Tiger, Mathias Almquist, Viktor Almquist and Niklas Carlsson. 2018.
Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs.
In Proceedings of the 2nd Network Traffic Measurement and Analysis Conference (TMA), pages 1–8. ISBN: 978-3-903176-09-6, 978-1-5386-7152-8.
DOI: 10.23919/TMA.2018.8506531.
Note: Funding agencies:  Swedish Research Council (VR); National Graduate School in Computer Science, Sweden (CUGS) Swedish Research Council (VR); National Graduate School in Computer Science, Sweden (CUGS)

With Twitter and other microblogging services, users can easily express their opinion and ideas in short text messages. A recent trend is that users use the real-time property of these services to share their opinions and thoughts as events unfold on TV or in the real world. In the context of TV broadcasts, Twitter (over a mobile device, for example) is referred to as a second screen. This paper presents the first characterization of the second screen usage over the playoffs of a major sports league. We present both temporal and spatial analysis of the Twitter usage during the end of the National Hockey League (NHL) regular season and the 2015 Stanley Cup playoffs. Our analysis provides insights into the usage patterns over the full 72-day period and with regards to in-game events such as goals, but also with regards to geographic biases. Quantifying these biases and the significance of specific events, we then discuss and provide insights into how the playoff dynamics may impact advertisers and third-party developers that try to provide increased personalization.

[577] Joel Odd and Emil Theologou. 2018.
Utilize OCR text to extract receipt data and classify receipts with common Machine Learning algorithms.
Student Thesis. 13 pages. ISRN: LIU-IDA/LITH-EX-G--18/043‚ÄĒSE.

This study investigated if it was feasible to use machine learning tools on OCR extracted text data to classify receipts and extract specific data points. Two OCR tools were evaluated, the first was Azure Computer Vision API and the second was Google Drive REST Api, where Google Drive REST Api was the main OCR tool used in the project because of its impressive performance. The classification task mainly tried to predict which of five given categories the receipts belongs to, and also a more challenging task of predicting specific subcategories inside those five larger categories. The data points we where trying to extract was the date of purchase on the receipt and the total price of the transaction. The classification was mainly done with the help of scikit-learn, while the extraction of data points was achieved by a simple custom made N-gram model.The results were promising with about 94 % cross validation score for classifying receipts based on category with the help of a LinearSVC classifier. Our custom model was successful in 72 % of cases for the price data point while the results for extracting the date was less successful with an accuracy of 50 %, which we still consider very promising given the simplistic nature of the custom model.

[576] Full text  Fredrik Heintz and Linda Mannila. 2018.
Computational Thinking for All - An Experience Report on Scaling up Teaching Computational Thinking to All Students in a Major City in Sweden.
In SIGCSE '18: Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE), pages 137–142. Association for Computing Machinery (ACM). ISBN: 978-1-4503-5103-4.
DOI: 10.1145/3159450.3159586.

The Swedish government has recently introduced digital competence including programming in the Swedish K-9 curriculum starting no later than fall 2018. This means that 100 000 teachers need to learn programming and digital competence in less than a year. In this paper we report on our experience working with professional teacher training in Sweden's fifth largest city. The city has about 150 000 inhabitants and about 50 schools with about 14 000 students in primary education. The project has been carried out in close cooperation with the municipality.The work started in the fall of 2014 with a pilot study with 10 teachers in different subjects that was carried out during spring 2015. The pilot study was successful as the teachers were able to introduce activities related to programming and computational thinking in their subjects after only two half day workshops. The next step was to scale this up to include all the schools in the city. As expected, this turned out to be a larger challenge. More than 70 teachers were involved in the second part of the project. Some of the lessons learned are that it is quite easy to provide teacher training, but harder to get teachers to actually change their teaching and even more challenging to get teachers to help their colleagues introduce programming or computational thinking in their teaching.Based on our experience we draw some general conclusions and make suggestions for how to scale up the teaching of programming and computational thinking to all.

2017
[575] Lukasz Bialek, Barbara Dunin-Keplicz and Andrzej Szalas. 2017.
Rule-Based Reasoning with Belief Structures.
In FOUNDATIONS OF INTELLIGENT SYSTEMS, ISMIS 2017, pages 229–239. In series: Lecture Notes in Artificial Intelligence #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-319-60438-1, 978-3-319-60437-4.
DOI: 10.1007/978-3-319-60438-1_23.
Note: Funding Agencies|Polish National Science Centre grant [2015/19/B/ST6/02589]

This paper introduces 4QL(Bel), a four-valued rule language designed for reasoning with paraconsistent and paracomplete belief bases as well as belief structures. Belief bases consist of finite sets of ground literals providing (partial and possibly inconsistent) complementary or alternative views of the world. As introduced earlier, belief structures consist of constituents, epistemic profiles and consequents. Constituents and consequents are belief bases playing different roles. Agents perceive the world forming their constituents, which are further transformed into consequents via the agents or groups epistemic profile. In order to construct 4QL(Bel), we extend 4QL, a four-valued rule language permitting for many forms of reasoning, including doxastic reasoning. Despite the expressiveness of 4QL(Bel), we show that its tractability is retained.

[574] Francesco Luca De Angelis, Giovanna Di Marzo Serugendo, Barbara Dunin-Keplicz and Andrzej Szalas. 2017.
Heterogeneous Approximate Reasoning with Graded Truth Values.
In ROUGH SETS, pages 61–82. In series: Lecture Notes in Artificial Intelligence #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-319-60837-2, 978-3-319-60836-5.
DOI: 10.1007/978-3-319-60837-2_6.
Note: Funding Agencies|Polish National Science Centre [2015/19/B/ST6/02589]

This paper is devoted to paraconsistent approximate reasoning with graded truth-values. In the previous research we introduced a family of many-valued logics parameterized by a variable number of truth/falsity grades together with a corresponding family of rule languages with tractable query evaluation. Such grades are shown here to be a natural qualitative counterpart of quantitative measures used in various forms of approximate reasoning. The developed methodology allows one to obtain a framework unifying heterogeneous reasoning techniques, providing also the logical machinery to resolve partial and incoherent information that may arise after unification. Finally, we show the introduced framework in action, emphasizing its expressiveness in handling heterogeneous approximate reasoning in realistic scenarios.

[573] Full text  Daniel de Leng and Fredrik Heintz. 2017.
Towards Adaptive Semantic Subscriptions for Stream Reasoning in the Robot Operating System.
In 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), pages 5445–5452. In series: IEEE International Conference on Intelligent Robots and Systems #??. IEEE. ISBN: 978-1-5386-2682-5.
DOI: 10.1109/IROS.2017.8206440.
Note: Funding Agencies|National Graduate School in Computer Science, Sweden (CUGS); Swedish Aeronautics Research Council [NFFP6]; Swedish Foundation for Strategic Research (SSF) project CUAS; Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT Excellence Center at Linkoping-Lund for Information Technology

Modern robotic systems often consist of a growing set of information-producing components that need to be appropriately connected for the system to function properly. This is commonly done manually or through relatively simple scripts by specifying explicitly which components to connect. However, this process is cumbersome and error-prone, does not scale well as more components are introduced, and lacks flexibility and robustness at run-time. This paper presents an algorithm for setting up and maintaining implicit subscriptions to information through its semantics rather than its source, which we call semantic subscriptions. The proposed algorithm automatically reconfigures the system when necessary in response to changes at run-time, making the semantic subscriptions adaptive to changing circumstances. To illustrate the effectiveness of adaptive semantic subscriptions, we present a case study with two SoftBank Robotics NAO robots for handling the cases when a component stops working and when new components, in this case a second robot, become available. The solution has been implemented as part of a stream reasoning framework integrated with the Robot Operating System (ROS).

[572] Full text  Mariusz Wzorek, Cyrille Berger and Patrick Doherty. 2017.
A Framework for Safe Navigation of Unmanned Aerial Vehicles in Unknown Environments.
In 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), pages 11–20. IEEE. ISBN: 978-1-5386-0610-0.
DOI: 10.1109/ICSEng.2017.58.
Note: Funding Agencies|Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research [RIT 15-0097]

This paper presents a software framework which combines reactive collision avoidance control approach with path planning techniques for the purpose of safe navigation of multiple Unmanned Aerial Vehicles (UAVs) operating in unknown environments. The system proposed leverages advantages of using a fast local sense-and-react type control which guarantees real-time execution with computationally demanding path planning algorithms which generate globally optimal plans. A number of probabilistic path planning algorithms based on Probabilistic Roadmaps and Rapidly-Exploring Random Trees have been integrated. Additionally, the system uses a reactive controller based on Optimal Reciprocal Collision Avoidance (ORCA) for path execution and fast sense-and-avoid behavior. During the mission execution a 3D map representation of the environment is build incrementally and used for path planning. A prototype implementation on a small scale quad-rotor platform has been developed. The UAV used in the experiments was equipped with a structured-light depth sensor to obtain information about the environment in form of occupancy grid map. The system has been tested in a number of simulated missions as well as in real flights and the results of the evaluations are presented.

[571] Full text  Piotr Rudol and Patrick Doherty. 2017.
Bridging Reactive and Control Architectural Layers for Cooperative Missions Using VTOL Platforms.
In 2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), pages 21–32. IEEE. ISBN: 978-1-5386-0610-0.
DOI: 10.1109/ICSEng.2017.59.
Note: Funding Agencies|Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research (SymbiKcloud Project)

In this paper we address the issue of connecting abstract task definitions at a mission level with control functionalities for the purpose of performing autonomous robotic missions using multiple heterogenous platforms. The heterogeneity is handled by the use of a common vocabulary which consists of parametrized tasks such as fly-to, take-off, scan-area, or land. Each of the platforms participating in a mission supports a subset of the tasks by providing their platform-specific implementations. This paper presents a detailed description of an approach for implementing such platform-specific tasks. It is achieved using a flight-command based interface with setpoint generation abstraction layer for vertical take-off and landing platforms. We show that by using this highly expressive and easily parametrizable way of specifying and executing flight behaviors it is straightforward to implement a wide range of tasks. We describe the method in the context of a previously described robotics architecture which includes mission delegation and execution system based on a task specification language. We present results of an experimental flight using the proposed method.

[570] Timo Hinzmann, Thomas Stastny, Gianpaolo Conte, Patrick Doherty, Piotr Rudol, Mariusz Wzorek, Enric Galceran, Roland Siegwart and Igor Gilitschenski. 2017.
Collaborative 3D Reconstruction Using Heterogeneous UAVs: System and Experiments.
In 2016 INTERNATIONAL SYMPOSIUM ON EXPERIMENTAL ROBOTICS, pages 43–56. In series: Springer Proceedings in Advanced Robotics #??. SPRINGER INTERNATIONAL PUBLISHING AG. ISBN: 978-3-319-50115-4, 978-3-319-50114-7.
DOI: 10.1007/978-3-319-50115-4_5.
Note: Funding Agencies|European Commissions Seventh Framework Programme (FP7) [285417, 600958]

This paper demonstrates how a heterogeneous fleet of unmanned aerial vehicles (UAVs) can support human operators in search and rescue (SaR) scenarios. We describe a fully autonomous delegation framework that interprets the top-level commands of the rescue team and converts them into actions of the UAVs. In particular, the UAVs are requested to autonomously scan a search area and to provide the operator with a consistent georeferenced 3D reconstruction of the environment to increase the environmental awareness and to support critical decision-making. The mission is executed based on the individual platform and sensor capabilities of rotary-and fixed-wing UAVs (RW-UAV and FW-UAV respectively): With the aid of an optical camera, the FW-UAV can generate a sparse point-cloud of a large area in a short amount of time. A LiDAR mounted on the autonomous helicopter is used to refine the visual point-cloud by generating denser point-clouds of specific areas of interest. In this context, we evaluate the performance of point-cloud registration methods to align two maps that were obtained by different sensors. In our validation, we compare classical point-cloud alignment methods to a novel probabilistic data association approach that specifically takes the individual point-cloud densities into consideration.

[569] Simon Keisala. 2017.
Designing an Artificial Neural Network for state evaluation in Arimaa: Using a Convolutional Neural Network.
Student Thesis. 31 pages. ISRN: LIU-IDA/LITH-EX-G--17/024--SE.

Agents being able to play board games such as Tic Tac Toe, Chess, Go and Arimaa has been, and still is, a major difficulty in Artificial Intelligence. For the mentioned board games, there is a certain amount of legal moves a player can do in a specific board state. Tic Tac Toe have in average around 4-5 legal moves, with a total amount of 255168 possible games. Both Chess, Go and Arimaa have an increased amount of possible legal moves to do, and an almost infinite amount of possible games, making it impossible to have complete knowledge of the outcome.This thesis work have created various Neural Networks, with the purpose of evaluating the likelihood of winning a game given a certain board state. An improved evaluation function would compensate for the inability of doing a deeper tree search in Arimaa, and the anticipation is to compete on equal skills against another well-performing agent (meijin) having one less search depth.The results shows great potential. From a mere one hundred games against meijin, the network manages to separate good from bad positions, and after another one hundred games able to beat meijin with equal search depth.It seems promising that by improving the training and by testing different sizes for the neural network that a neural network could win even with one less search depth. The huge branching factor of Arimaa makes such an improvement of the evaluation beneficial, even if the evaluation would be 10 000 times more slow.

[568] Niclas Jonsson. 2017.
Implementation and testing of an FPT-algorithm for computing the h+ heuristic.
Student Thesis. 39 pages. ISRN: LIU-IDA/LITH-EX-G‚Äď17/077‚ÄďSE.

We have implemented and benchmarked an FPT-algorithm, that has two input parameters, k and w besides the input problem instance, which is a planing instance, in this thesis. The algorithm has an exponential running time as a function of these two parameters. The implemented algorithm computes the heuristic value h^+(s) of a state s that belongs to a state space, which originates from a strips instance. The purpose of the project was to test if the algorithm can be used to compute the heuristic function h^+, i.e. the delete-relaxation heuristic, in practice. The delete-relaxation heuristic value for some state is the length of the optimal solution from the state to a goal in the delete-relaxed-instance, which is the original instance without all its negative effects. Planning instances was benchmarked with the search algorithm A^* to test the algorithms practical value. The heuristic function blind was benchmarked together with A^* with the same instances so that we could compare the quality of the benchmark result for the implemented algorithm. The conclusion of the project was that the implemented algorithm is too slow to be used in practise.

[567] Full text  Fredrik Pršntare, Ingemar Ragnemalm and Fredrik Heintz. 2017.
An Algorithm for Simultaneous Coalition Structure Generation and Task Assignment.
In Bo An, Ana Bazzan, Jo√£o Leite, Serena Villata and Leendert van der Torre, editors, PRIMA 2017: Principles and Practice of Multi-Agent Systems 20th International Conference, Nice, France, October 30 ? November 3, 2017, Proceedings, pages 514–522. In series: Lecture Notes in Computer Science #10621. Springer. ISBN: 9783319691305, 9783319691312.
DOI: 10.1007/978-3-319-69131-2_34.

Groups of agents in multi-agent systems may have to cooperate to solve tasks efficiently, and coordinating such groups is an important problem in the field of artificial intelligence. In this paper, we consider the problem of forming disjoint coalitions and assigning them to independent tasks simultaneously, and present an anytime algorithm that efficiently solves the <em>simultaneous coalition structure generation and task assignment</em> problem. This NP-complete combinatorial optimization problem has many real-world applications, including forming cross-functional teams aimed at solving tasks. To evaluate the algorithm's performance, we extend established methods for synthetic problem set generation, and benchmark the algorithm using randomized data sets of varying distribution and complexity. Our results show that the presented algorithm efficiently finds optimal solutions, and generates high quality solutions when interrupted prior to finishing an exhaustive search. Additionally, we apply the algorithm to solve the problem of assigning agents to regions in a commercial computer-based strategy game, and empirically show that our algorithm can significantly improve the coordination and computational efficiency of agents in a real-time multi-agent system.

[566] Full text  Fredrik Heintz, Linda Mannila, Lars-Ňke Nordťn, Peter Parnes and Regnell BjŲrn. 2017.
Introducing Programming and Digital Competence in Swedish†K?9 Education.
In Valentina Dagienńó and Arto Hellas, editors, Informatics in Schools: Focus on Learning Programming: 10th International Conference on Informatics in Schools: Situation, Evolution, and Perspective (ISSEP), Helsinki, Finland, November 13-15, 2017, pages 117–128. In series: Lecture Notes in Computer Science #10696. Springer. ISBN: 9783319714820, 9783319714837.
DOI: 10.1007/978-3-319-71483-7_10.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

The role of computer science and IT in Swedish schools hasvaried throughout the years. In fall 2014, the Swedish government gavethe National Agency for Education (Skolverket) the task of preparing aproposal for K-9 education on how to better address the competencesrequired in a digitalized society. In June 2016, Skolverket handed overa proposal introducing digital competence and programming as interdisciplinarytraits, also providing explicit formulations in subjects such asmathematics (programming, algorithms and problem-solving), technology(controlling physical artifacts) and social sciences (fostering awareand critical citizens in a digital society). In March 2017, the governmentapproved the new curriculum, which needs to be implemented by fall 2018 at the latest. We present the new K-9 curriculum and put it ina historical context. We also describe and analyze the process of developingthe revised curriculum, and discuss some initiatives for how toimplement the changes.

[565] Full text  Daniel de Leng. 2017.
Spatio-Temporal Stream Reasoning with Adaptive State Stream Generation.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1783. LinkŲping University Electronic Press. 133 pages. ISBN: 9789176854761.
DOI: 10.3384/lic.diva-138645.
Note: The series name Linköping Studies in Science and Technology Licentiate Thesis is inocorrect. The correct series name is Linköping Studies in Science and Technology Thesis.
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A lot of today's data is generated incrementally over time by a large variety of producers. This data ranges from quantitative sensor observations produced by robot systems to complex unstructured human-generated texts on social media. With data being so abundant, making sense of these streams of data through reasoning is challenging. Reasoning over streams is particularly relevant for autonomous robotic systems that operate in a physical environment. They commonly observe this environment through incremental observations, gradually refining information about their surroundings. This makes robust management of streaming data and its refinement an important problem.Many contemporary approaches to stream reasoning focus on the issue of querying data streams in order to generate higher-level information by relying on well-known database approaches. Other approaches apply logic-based reasoning techniques, which rarely consider the provenance of their symbolic interpretations. In this thesis, we integrate techniques for logic-based spatio-temporal stream reasoning with the adaptive generation of the state streams needed to do the reasoning over. This combination deals with both the challenge of reasoning over streaming data and the problem of robustly managing streaming data and its refinement.The main contributions of this thesis are (1) a logic-based spatio-temporal reasoning technique that combines temporal reasoning with qualitative spatial reasoning; (2) an adaptive reconfiguration procedure for generating and maintaining a data stream required to perform spatio-temporal stream reasoning over; and (3) integration of these two techniques into a stream reasoning framework. The proposed spatio-temporal stream reasoning technique is able to reason with intertemporal spatial relations by leveraging landmarks. Adaptive state stream generation allows the framework to adapt in situations in which the set of available streaming resources changes. Management of streaming resources is formalised in the DyKnow model, which introduces a configuration life-cycle to adaptively generate state streams. The DyKnow-ROS stream reasoning framework is a concrete realisation of this model that extends the Robot Operating System (ROS). DyKnow-ROS has been deployed on the SoftBank Robotics NAO platform to demonstrate the system's capabilities in the context of a case study on run-time adaptive reconfiguration. The results show that the proposed system ‚Äď by combining reasoning over and reasoning about streams ‚Äď can robustly perform spatio-temporal stream reasoning, even when the availability of streaming resources changes.

[564] Fredrik Heintz and Fredrik LŲfgren. 2017.
LinkŲping Humanoids: Application RoboCup 2017 Standard Platform League.

This is the application for the RoboCup 2017 Standard Platform League from the Link¨oping Humanoids teamLinköping Humanoids participated in both RoboCup 2015 and 2016 with the intention of incrementally developing a good team by learning as much as possible. We significantly improved from 2015 to 2016, even though we still didn’t perform very well. Our main challenge is that we are building our software from the ground up using the Robot Operating System (ROS) as the integration and development infrastructure. When the system became overloaded, the ROS infrastructure became very unpredictable. This made it very hard to debug during the contest, so we basically had to remove things until the load was constantly low. Our top priority has since been to make the system stable and more resource efficient. This will take us to the next level.From the start we have been clear that our goal is to have a competitive team by 2017 since we are developing our own software from scratch we are very well aware that we needed time to build up the competence and the software infrastructure. We believe we are making good progress towards this goal. The team of about 10 students has been very actively working during the fall with weekly workshops and bi-weekly one day hackathons.

[563] Olov Andersson. 2017.
Methods for Scalable and Safe Robot Learning.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1780. LinkŲping University Electronic Press. 37 pages. ISBN: 9789176854907.
DOI: 10.3384/lic.diva-138398.
Fulltext: https://doi.org/10.3384/lic.diva-138398
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Robots are increasingly expected to go beyond controlled environments in laboratories and factories, to enter real-world public spaces and homes. However, robot behavior is still usually engineered for narrowly defined scenarios. To manually encode robot behavior that works within complex real world environments, such as busy work places or cluttered homes, can be a daunting task. In addition, such robots may require a high degree of autonomy to be practical, which imposes stringent requirements on safety and robustness. \setlength{\parindent}{2em}\setlength{\parskip}{0em}The aim of this thesis is to examine methods for automatically learning safe robot behavior, lowering the costs of synthesizing behavior for complex real-world situations. To avoid task-specific assumptions, we approach this from a data-driven machine learning perspective. The strength of machine learning is its generality, given sufficient data it can learn to approximate any task. However, being embodied agents in the real-world, robots pose a number of difficulties for machine learning. These include real-time requirements with limited computational resources, the cost and effort of operating and collecting data with real robots, as well as safety issues for both the robot and human bystanders.While machine learning is general by nature, overcoming the difficulties with real-world robots outlined above remains a challenge. In this thesis we look for a middle ground on robot learning, leveraging the strengths of both data-driven machine learning, as well as engineering techniques from robotics and control. This includes combing data-driven world models with fast techniques for planning motions under safety constraints, using machine learning to generalize such techniques to problems with high uncertainty, as well as using machine learning to find computationally efficient approximations for use on small embedded systems.We demonstrate such behavior synthesis techniques with real robots, solving a class of difficult dynamic collision avoidance problems under uncertainty, such as induced by the presence of humans without prior coordination. Initially using online planning offloaded to a desktop CPU, and ultimately as a deep neural network policy embedded on board a 7 quadcopter.

[562] Full text  Mariusz Wzorek, Piotr Rudol, Gianpaolo Conte and Patrick Doherty. 2017.
LinkBoard: Advanced Flight Control System for Micro Unmanned Aerial Vehicles.
In 2017 2ND INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTICS ENGINEERING (ICCRE2017). IEEE. ISBN: 978-1-5090-3774-2.
DOI: 10.1109/ICCRE.2017.7935051.
Note: Funding Agencies|Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT network organization for Information and Communication Technology; Swedish Foundation for Strategic Research [RIT 15-0097]

This paper presents the design and development of the LinkBoard, an advanced flight control system for micro Unmanned Aerial Vehicles (UAVs). Both hardware and software architectures are presented. The LinkBoard includes four processing units and a full inertial measurement unit. In the basic configuration, the software architecture includes a fully configurable set of control modes and sensor fusion algorithms for autonomous UAV operation. The system proposed allows for easy integration with new platforms, additional external sensors and a flexibility to trade off computational power, weight and power consumption. Due to the available onboard computational power, it has been used for computationally demanding applications such as the implementation of an autonomous indoor vision-based navigation system with all computations performed onboard. The autopilot has been manufactured and deployed on multiple UAVs. Examples of UAV systems built with the LinkBoard and their applications are presented, as well as an in-flight experimental performance evaluation of a newly developed attitude estimation filter.

[561] Henrik Phung. 2017.
Software developers? performance awareness.
Student Thesis. 49 pages. ISRN: LIU-IDA/LITH-EX-A--17/016--SE.

Automated tests and non-functional requirements are two widely used terms in the software development sector. Both are essential for software development teams but rarely mentioned together. Today, most software development teams are utilizing the development practice continuous integration. A method where software is built in iterations and in each iteration small chunks of code are merged into the main repository. Continuous integration requires automated tests to verify that each chunk of code is compatible with the main chunk. Automated test is essential for continuous integration to detect anomalies in each chunk of code. Customer satisfaction is a result of how well the delivered product performs in terms of non-functional requirements. Although the term ‚Äúnon-functional requirement‚ÄĚ has not been formally defined and the existing definitions are diverse. In this thesis, we define the non-functional requirement, response time with help from a user-centered evaluation of responsiveness study. We create a test suite that can be ran on an automated build with focus on user-action-response. Based on the test result and a conducted survey, we evaluate how aware developers are when it comes to causes to performance issues.

[560] Full text  Daniel Artchounin. 2017.
Tuning of machine learning algorithms for automatic bug assignment.
Student Thesis. 135 pages. ISRN: LIU-IDA/LITH-EX-A--17/022--SE.

In software development projects, bug triage consists mainly of assigning bug reports to software developers or teams (depending on the project). The partial or total automation of this task would have a positive economic impact on many software projects. This thesis introduces a systematic four-step method to find some of the best configurations of several machine learning algorithms intending to solve the automatic bug assignment problem. These four steps are respectively used to select a combination of pre-processing techniques, a bug report representation, a potential feature selection technique and to tune several classifiers. The aforementioned method has been applied on three software projects: 66 066 bug reports of a proprietary project, 24 450 bug reports of Eclipse JDT and 30 358 bug reports of Mozilla Firefox. 619 configurations have been applied and compared on each of these three projects. In production, using the approach introduced in this work on the bug reports of the proprietary project would have increased the accuracy by up to 16.64 percentage points.

[559] Fredrik Pršntare. 2017.
Simultaneous coalition formation and task assignment in a real-time strategy game.
Student Thesis. 65 pages. ISRN: LIU-IDA/LITH-EX-A--17/032--SE.

In this thesis we present an algorithm that is designed to improve the collaborative capabilities of agents that operate in real-time multi-agent systems. Furthermore, we study the coalition formation and task assignment problems in the context of real-time strategy games. More specifically, we design and present a novel anytime algorithm for multi-agent cooperation that efficiently solves the simultaneous coalition formation and assignment problem, in which disjoint coalitions are formed and assigned to independent tasks simultaneously. This problem, that we denote the problem of collaboration formation, is a combinatorial optimization problem that has many real-world applications, including assigning disjoint groups of workers to regions or tasks, and forming cross-functional teams aimed at solving specific problems.The algorithm's performance is evaluated using randomized artificial problems sets of varying complexity and distribution, and also using Europa Universalis 4 ‚Äď a commercial strategy game in which agents need to cooperate in order to effectively achieve their goals. The agents in such games are expected to decide on actions in real-time, and it is a difficult task to coordinate them. Our algorithm, however, solves the coordination problem in a structured manner.The results from the artificial problem sets demonstrates that our algorithm efficiently solves the problem of collaboration formation, and does so by automatically discarding suboptimal parts of the search space. For instance, in the easiest artificial problem sets with 12 agents and 8 tasks, our algorithm managed to find optimal solutions after only evaluating approximately 0.000003% of the possible solutions. In the hardest of the problem sets with 12 agents and 8 tasks, our algorithm managed to find a 80% efficient solution after only evaluating approximately 0.000006% of the possible solutions.

[558] Full text  Tova Linder and Ola Jigin. 2017.
Organ Detection and Localization in Radiological Image Volumes.
Student Thesis. 88 pages. ISRN: LIU-IDA/LITH-EX-A--17/024--SE.

Using Convolutional Neural Networks for classification of images and for localization and detection of objects in images is becoming increasingly popular. Within radiology a huge amount of image data is produced and meta data containing information of what the images depict is currently added manually by a radiologist. To aid in streamlining physician’s workflow this study has investigated the possibility to use Convolutional Neural Networks (CNNs) that are pre-trained on natural images to automatically detect the presence and location of multiple organs and body-parts in medical CT images. The results show promise for multiclass classification with an average precision 89.41% and average recall 86.40%. This also confirms that a CNN that is pre-trained on natural images can be succesfully transferred to solve a different task. It was also found that adding additional data to the dataset does not necessarily result in increased precision and recall or decreased error rate. It is rather the type of data and used preprocessing techniques that matter.

[557] Full text  Elena Moral Lůpez. 2017.
Muting pattern strategy for positioning in cellular networks.
Student Thesis. 65 pages. ISRN: LIU-IDA/LITH-EX-A--17/018--SE.

Location Based Services (LBS) calculate the position of the user for different purposes like advertising and navigation. Most importantly, these services are also used to help emergency services by calculating the position of the person that places the emergency phone call. This has introduced a number of requirements on the accuracy of the measurements of the position. Observed Time Difference of Arrival (OTDOA) is the method used to estimate the position of the user due to its high accuracy. Nevertheless, this method relies on the correct reception of so called positioning signals, and therefore the calculations can suffer from errors due to interference between the signals. To lower the probability of interference, muting patterns can be used. These methods can selectively mute certain signals to increase the signal to interference and noise ratio (SINR) of others and therefore the number of signals detected. In this thesis, a simulation environment for the comparison of the different muting patterns has been developed. The already existing muting patterns have been simulated and compared in terms of number of detected nodes and SINR values achieved. A new muting pattern has been proposed and compared to the others. The results obtained have been presented and an initial conclusion on which of the muting patterns offers the best performance has been drawn.

[556] Petra ÷hlin. 2017.
Prioritizing Tests with Spotify?s Test & Build Data using History-based, Modification-based & Machine Learning Approaches.
Student Thesis. 43 pages. ISRN: LIU-IDA/LITH-EX-A--2017/021--SE.

This thesis intends to determine the extent to which machine learning can be used to solve the regression test prioritization (RTP) problem. RTP is used to order tests with respect to probability of failure. This will optimize for a fast failure, which is desirable if a test suite takes a long time to run or uses a significant amount of computational resources. A common machine learning task is to predict probabilities; this makes RTP an interesting application of machine learning. A supervised learning method is investigated to train a model to predict probabilities of failure, given a test case and a code change. The features investigated are chosen based on previous research of history- based and modification-based RTP. The main motivation for looking at these research areas is that they resemble the data provided by Spotify. The result of the report shows that it is possible to improve how tests run with RTP using machine learning. Nevertheless, a much simpler history- based approach is the best performing approach. It is looking at the history of test results, the more failures recorded for the test case over time, the higher priority it gets. Less is sometimes more.

[555] Full text  Joakim Gylling. 2017.
Transition-Based Dependency Parsing with Neural Networks.
Student Thesis. 10 pages. ISRN: LIU-IDA/LITH-EX-G--17/011--SE.

Dependency parsing is important in contemporary speech and language processing systems. Current dependency parsers typically use the multi-class perceptron machine learning component, which classifies based on millions of sparse indicator features, making developing and maintaining these systems expensive and error-prone. This thesis aims to explore whether replacing the multi-class perceptron component with an artificial neural network component can alleviate this problem without hurting performance, in terms of accuracy and efficiency. A simple transition-based dependency parser using the artificial neural network (ANN) as the classifier is written in Python3 and the same program with the classifier replaced by a multi-class perceptron component is used as a baseline. The results show that the ANN dependency parser provides slightly better unlabeled attachment score with only the most basic atomic features, eliminating the need for complex feature engineering. However, it is about three times slower and the training time required for the ANN is significantly longer.

[554] Full text  Maximilian Bragazzi Ihrťn and Henrik Ingbrant BjŲrs. 2017.
Visualizing atmospheric data on a mobile platform.
Student Thesis. 10 pages. ISRN: LIU-IDA/LITH-EX-G--17/010--SE.

Weather data is important for almost everyone today. Thedaily weather report, home thermometers, and a lot of otherthings affect our every day life. In order to develop betterand more efficient equipment, tools and algorithms, thepeople working with this data need to be able to access it inan easily accessible and easy to read format. In thisresearch, methods of visualizing data on mobile platformsare evaluated based on what researchers in the field wants,since their respective fields might want to use very specificvisualizations. The implementability of these visualizationsare then evaluated, based on the implementations madethroughout this paper. The results show that the researchersknow what they want, and that what they want isimplementable on mobile platforms given some limitationscaused by performance.

[553] Full text  Fredrik Jonsťn and Alexander Stolpe. 2017.
The feasibility and practicality of a generic social media library.
Student Thesis. 8 pages. ISRN: LIU-IDA/LITH-EX-G--17/009--SE.

Many people today use social media in one way or another, and many of these platforms have released APIs developers can use to integrate social media in their applications. As many of these platforms share a lot of functionality we see a need for developing a library, to contain these, and ease the development process when working with the platforms. The purpose of this paper is to find common functionality and explore the possibility of generalization in this regard. We first look for common denominators between the top social media networks, and using this information we attempt to make an implementation to evaluate the practicality. After the development process we analyze our findings and discuss the usability and maintainability of such a library. Our findings show that the current state of the studied APIs are not suitable for generalization.

[552] Full text  Olov Andersson, Mariusz Wzorek and Patrick Doherty. 2017.
Deep Learning Quadcopter Control via Risk-Aware Active Learning.
In Satinder Singh and Shaul Markovitch, editors, Proceedings of The Thirty-first AAAI Conference on Artificial Intelligence (AAAI), pages 3812–3818. In series: Proceedings of the AAAI Conference on Artificial Intelligence #5. AAAI Press. ISBN: 978-1-57735-784-1.

Modern optimization-based approaches to control increasingly allow automatic generation of complex behavior from only a model and an objective. Recent years has seen growing interest in fast solvers to also allow real-time operation on robots, but the computational cost of such trajectory optimization remains prohibitive for many applications. In this paper we examine a novel deep neural network approximation and validate it on a safe navigation problem with a real nano-quadcopter. As the risk of costly failures is a major concern with real robots, we propose a risk-aware resampling technique. Contrary to prior work this active learning approach is easy to use with existing solvers for trajectory optimization, as well as deep learning. We demonstrate the efficacy of the approach on a difficult collision avoidance problem with non-cooperative moving obstacles. Our findings indicate that the resulting neural network approximations are least 50 times faster than the trajectory optimizer while still satisfying the safety requirements. We demonstrate the potential of the approach by implementing a synthesized deep neural network policy on the nano-quadcopter microcontroller.

[551] Full text  Oleg Burdakov, Jonas KvarnstrŲm and Patrick Doherty. 2017.
Optimal scheduling for replacing perimeter guarding unmanned aerial vehicles.
Annals of Operations Research, 249(1):163–174. Springer.
DOI: 10.1007/s10479-016-2169-5.
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Guarding the perimeter of an area in order to detect potential intruders is an important task in a variety of security-related applications. This task can in many circumstances be performed by a set of camera-equipped unmanned aerial vehicles (UAVs). Such UAVs will occasionally require refueling or recharging, in which case they must temporarily be replaced by other UAVs in order to maintain complete surveillance of the perimeter. In this paper we consider the problem of scheduling such replacements. We present optimal replacement strategies and justify their optimality.

2016
[550] Fredrik Heintz and Fredrik LŲfgren. 2016.
LinkŲping Humanoids: Application RoboCup 2016 Standard Platform League.
In , pages 1–2.
Qualification Video for RoboCup Standard Platform League 2016: https://www.youtube.com/watch?v=Og8Azj2Y...
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

This is the application for the RoboCup 2016 Standard Platform League from the Linköping Humanoids team.Linköping Humanoids participated in RoboCup 2015. We didn’t do very well, but we learned a lot. When we arrived nothing worked. However, we fixed more and more of the open issues and managed to play a draw in our final game. We also participated in some of the technical challenges and scored some points. At the end of the competition we had a working team. This was both frustrating and rewarding. Analyzing the competition we have identified both what we did well and the main issues that we need to fix. One important lesson is that it takes time to develop a competitive RoboCup SPL team. Weare dedicated to improving our performance over time in order to be competitive in 2017.

[549] Fredrik LŲfgren. 2016.
How may robots affect the labour market in the near future?.
In Andreas Bergstr√∂m and Karl Wennberg, editors, Machines, jobs and equality: Technological changes and labour markets in Europe, pages 105–134. The European Liberal Forum (ELF). ISBN: 9789187379369.
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This chapter discusses how different applications for robots will affect the labour market in the near future. Near future refers to the next 10-50 years. It is likely that several occupations will disappear, but new ones will also emerge. However, we claim that the net result will be negative, which means that we will have higher unemployment. These effects will not happen overnight, and not all occupations will be affected. But, this will happen for a sufficient amount of the population for it to become a problem for society.The observations made in this chapter are not from the point of view of a social scientist, but that of a roboticist. The observations are taken together with readings of scientific literature on automation. I do not claim to have answers to the economic and social scientific problems thrown up, but to raise a set of critical questions for the reader.All the examples in this chapter are real technologies that exist, not just in science-fiction or future technology. However, most of the examples are still in their research stage and are either not available for the general public, or still very expensive.No one can predict the future in detail, but this chapter tries to provide a scenario of the future of different kinds of occupations through the perspective of the field of robotics. I have been developing robots for 15 years and will use some examples that I have constructed, but also examples from other roboticists. The chapter does not discuss the risks of automation for all occupations, but instead focuses on blue-collar workers, such as machine operators, the transportation sector with the advent of driverless cars, white-collar workers in offices, skilled professions in the legal and medical spheres, and creative workers.

[548] Gustav Hšger, Goutam Bhat, Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg, Piotr Rudol and Patrick Doherty. 2016.
Combining Visual Tracking and Person Detection for Long Term Tracking on a UAV.
In Proceedings of the 12th International Symposium on Advances in Visual Computing. In series: Lecture Notes in Computer Science #??. Springer. ISBN: 978-3-319-50834-4, 978-3-319-50835-1.
DOI: 10.1007/978-3-319-50835-1_50.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Visual object tracking performance has improved significantly in recent years. Most trackers are based on either of two paradigms: online learning of an appearance model or the use of a pre-trained object detector. Methods based on online learning provide high accuracy, but are prone to model drift. The model drift occurs when the tracker fails to correctly estimate the tracked object’s position. Methods based on a detector on the other hand typically have good long-term robustness, but reduced accuracy compared to online methods.Despite the complementarity of the aforementioned approaches, the problem of fusing them into a single framework is largely unexplored. In this paper, we propose a novel fusion between an online tracker and a pre-trained detector for tracking humans from a UAV. The system operates at real-time on a UAV platform. In addition we present a novel dataset for long-term tracking in a UAV setting, that includes scenarios that are typically not well represented in standard visual tracking datasets.

[547] Patrick Doherty and Andrzej Szalas. 2016.
An Entailment Procedure for Kleene Answer Set Programs.
In Sombattheera C., Stolzenburg F., Lin F., Nayak A., editors, Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2016., pages 24–37. In series: Lecture Notes in Computer Science #10053. Springer. ISBN: 978-3-319-49396-1, 978-3-319-49397-8.
DOI: 10.1007/978-3-319-49397-8_3.

Classical Answer Set Programming is a widely known knowledge representation framework based on the logic programming paradigm that has been extensively studied in the past decades. Semantic theories for classical answer sets are implicitly three-valued in nature, yet with few exceptions, computing classical answer sets is based on translations into classical logic and the use of SAT solving techniques. In this paper, we introduce a variation of Kleene three-valued logic with strong connectives, R3\" role=\"presentation\"&gt;R3, and then provide a sound and complete proof procedure for R3\" role=\"presentation\"&gt;R3 based on the use of signed tableaux. We then define a restriction on the syntax of R3\" role=\"presentation\"&gt;R3 to characterize Kleene ASPs. Strongly-supported models, which are a subset of R3\" role=\"presentation\"&gt;R3 models are then defined to characterize the semantics of Kleene ASPs. A filtering technique on tableaux for R3\" role=\"presentation\"&gt;R3 is then introduced which provides a sound and complete tableau-based proof technique for Kleene ASPs. We then show a translation and semantic correspondence between Classical ASPs and Kleene ASPs, where answer sets for normal classical ASPs are equivalent to strongly-supported models. This implies that the proof technique introduced can be used for classical normal ASPs as well as Kleene ASPs. The relation between non-normal classical and Kleene ASPs is also considered.

[546] Full text  Patrick Doherty, Jonas KvarnstrŲm and Andrzej Szalas. 2016.
Iteratively-Supported Formulas and Strongly Supported Models for Kleene Answer Set Programs.
In Michael, Loizos; Kakas, Antonis, editors, Logics in Artificial Intelligence: 15th European Conference, JELIA 2016, Larnaca, Cyprus, November 9-11, 2016, Proceedings, pages 536–542. In series: Lecture Notes in Computer Science #10021. Springer Publishing Company. ISBN: 978-3-319-48757-1, 978-3-319-48758-8.
DOI: 10.1007/978-3-319-48758-8_36.

In this extended abstract, we discuss the use of iteratively-supported formulas (ISFs) as a basis for computing strongly-supported models for Kleene Answer Set Programs (ASPK). ASPK programs have a syntax identical to classical ASP programs. The semantics of ASPK programs is based on the use of Kleene three-valued logic and strongly-supported models. For normal ASPK programs, their strongly supported models are identical to classical answer sets using stable model semantics. For disjunctive ASPK programs, the semantics weakens the minimality assumption resulting in a classical interpretation for disjunction. We use ISFs to characterize strongly-supported models and show that they are polynomially bounded.

[545] Full text  Fredrik Heintz, Linda Mannila and Tommy Fšrnqvist. 2016.
A Review of Models for Introducing Computational Thinking, Computer Science and Computing in K-12 Education.
In Proceedings of the 46th Frontiers in Education (FIE). In series: Frontiers in Education Conference #??. IEEE. ISBN: 978-1-5090-1790-4, 978-1-5090-1791-1.
DOI: 10.1109/FIE.2016.7757410.

Computing is becoming ever increasingly importantto our society. However, computing in primary and secondaryeducation has not been well developed. Computing has traditionallybeen primarily a university level discipline and there areno widely accepted general standards for what computing at K‚Äď12 level entails. Also, as the interest in this area is rather new,the amount of research conducted in the field is still limited. Inthis paper we review how 10 different countries have approachedintroducing computing into their K‚Äď12 education. The countriesare Australia, England, Estonia, Finland, New Zealand, Norway,Sweden, South Korea, Poland and USA.The studied countries either emphasize digital competenciestogether with programming or the broader subject of computingor computer science. Computational thinking is rarely mentionedexplicitly, but the ideas are often included in some form. Themost common model is to make it compulsory in primary schooland elective in secondary school. A few countries have made itcompulsory in both. While some countries have only introducedit in secondary school.

[544] Full text  Piotr Rudol and Patrick Doherty. 2016.
Bridging the mission-control gap: A flight command layer for mediating flight behaviours and continuous control.
In 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pages 304–311. In series: 2016 IEEE INTERNATIONAL SYMPOSIUM ON SAFETY, SECURITY, AND RESCUE ROBOTICS (SSRR) #??. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781509043491, 9781509043507.
DOI: 10.1109/SSRR.2016.7784320.

The use of UAVs, in particular, micro VTOL UAVs, is becoming prevalent in emergency rescue and security applications, among others. In these applications, the platforms are tightly coupled to the human users and these applications require great flexibility in the interaction between the platforms and such users. During operation, one continually switches between manual, semi-autonomous and autonomous operation, often re-parameterising, breaking in, pausing, and resuming missions. One is in continual need of modifying existing elementary actions and behaviours such as FlyTo and TrackObject, and seamlessly switching between such operations. This paper proposes a flight command and setpoint abstraction layer that serves as an interface between continuous control and higher level elementary flight actions and behaviours. Introduction of such a layer into an architecture offers a versatile and flexible means of defining flight behaviours and dynamically parameterising them in the field, in particular where human users are involved. The system proposed is implemented in prototype and the paper provides experimental validation of the use and need for such abstractions in system architectures.

[543] Full text  Marcus Johansson. 2016.
Online Whole-Body Control using Hierarchical Quadratic Programming: Implementation and Evaluation of the HiQP Control Framework.
Student Thesis. 76 pages. ISRN: LIU-IDA/LITH-EX-A--16/056--SE.

The application of local optimal control is a promising paradigm for manipulative robot motion generation.In practice this involves instantaneous formulations of convex optimization problems depending on the current joint configuration of the robot and the environment.To be effective, however, constraints have to be carefully constructed as this kind of motion generation approach has a trade-off of completeness.Local optimal solvers, which are greedy in a temporal sense, have proven to be significantly more effective computationally than classical grid-based or sampling-based planning approaches.In this thesis we investigate how a local optimal control approach, namely the task function approach, can be implemented to grant high usability, extendibility and effectivity.This has resulted in the HiQP control framework, which is compatible with ROS, written in C++.The framework supports geometric primitives to aid in task customization by the user.It is also modular as to what communication system it is being used with, and to what optimization library it uses for finding optimal controls.We have evaluated the software quality of the framework according to common quantitative methods found in the literature.We have also evaluated an approach to perform tasks using minimal jerk motion generation with promising results.The framework also provides simple translation and rotation tasks based on six rudimentary geometric primitives.Also, task definitions for specific joint position setting, and velocity limitations were implemented.

[542] Full text  Mattias Tiger and Fredrik Heintz. 2016.
Stream Reasoning using Temporal Logic and Predictive Probabilistic State Models.
In 23nd International Symposium on Temporal Representation and Reasoning (TIME), 2016. IEEE Computer Society.
Note: Presented at the 23nd International Symposium on Temporal Representation and Reasoning (TIME) at the Technical University of Denmark (DTU), Denmark, the 19th October 2016.

Integrating logical and probabilistic reasoning and integrating reasoning over observations and predictions are two important challenges in AI. In this paper we propose P-MTL as an extension to Metric Temporal Logic supporting temporal logical reasoning over probabilistic and predicted states. The contributions are (1) reasoning over uncertain states at single time points, (2) reasoning over uncertain states between time points, (3) reasoning over uncertain predictions of future and past states and (4) a computational environment formalism that ground the uncertainty in observations of the physical world. Concrete robot soccer examples are given.

[541] Full text  Cyrille Berger, Mariusz Wzorek, Jonas KvarnstrŲm, Gianpaolo Conte, Patrick Doherty and Alexander Eriksson. 2016.
Area Coverage with Heterogeneous UAVs using Scan Patterns.
In 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR): proceedings. In series: 2016 IEEE INTERNATIONAL SYMPOSIUM ON SAFETY, SECURITY, AND RESCUE ROBOTICS (SSRR) #??. IEEE Robotics and Automation Society. ISBN: 978-1-5090-4349-1.
DOI: 10.1109/SSRR.2016.7784325.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

In this paper we consider a problem of scanningan outdoor area with a team of heterogeneous Unmanned AirVehicles (UAVs) equipped with different sensors (e.g. LIDARs).Depending on the availability of the UAV platforms and themission requirements there is a need to either minimise thetotal mission time or to maximise certain properties of thescan output, such as the point cloud density. The key challengeis to divide the scanning task among UAVs while taking intoaccount the differences in capabilities between platforms andsensors. Additionally, the system should be able to ensure thatconstraints such as limit on the flight time are not violated.We present an approach that uses an optimisation techniqueto find a solution by dividing the area between platforms,generating efficient scan trajectories and selecting flight andscanning parameters, such as velocity and flight altitude. Thismethod has been extensively tested on a large set of randomlygenerated scanning missions covering a wide range of realisticscenarios as well as in real flights.

[540] Full text  Mattias Tiger and Fredrik Heintz. 2016.
Stream Reasoning using Temporal Logic and Predictive Probabilistic State Models.
In 23nd International Symposium on Temporal Representation and Reasoning (TIME), 2016, pages 196–205. IEEE Computer Society. ISBN: 978-1-5090-3825-1.
DOI: 10.1109/TIME.2016.28.
Note: Presented at the 23nd International Symposium on Temporal Representation and Reasoning (TIME) at the Technical University of Denmark (DTU), Denmark, the 19th October 2016.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Integrating logical and probabilistic reasoning and integrating reasoning over observations and predictions are two important challenges in AI. In this paper we propose P-MTL as an extension to Metric Temporal Logic supporting temporal logical reasoning over probabilistic and predicted states. The contributions are (1) reasoning over uncertain states at single time points, (2) reasoning over uncertain states between time points, (3) reasoning over uncertain predictions of future and past states and (4) a computational environment formalism that ground the uncertainty in observations of the physical world. Concrete robot soccer examples are given.

[539] Jose Renato Garcia Braga, Gianpaolo Conte, Patrick Doherty, Haroldo Fraga Campos Velho and Elcio Hideiti Shiguemori. 2016.
An Image Matching System for Autonomous UAV Navigation Based on Neural Network.
In 14th International Conference on Control, Automation, Robotics and Vision (ICARCV 2016). In series: International Conference on Control Automation Robotics and Vision #??. ISBN: 978-1-5090-3549-6, 978-1-5090-3550-2.
DOI: 10.1109/ICARCV.2016.7838775.
Note: Funding agencies:This work was carried out with support from CNPq - National Counsel of Technological and Scientific Development - Brazil. This work is partially supported by the Swedish Research Council (VR) Linnaeus Center CADICS, ELLIIT, and the Swedish Foundation for Strategic Research (CUAS Project, SymbiKCloud Project).

This paper proposes an image matching system using aerial images, captured in flight time, and aerial geo-referenced images to estimate the Unmanned Aerial Vehicle (UAV) position in a situation of Global Navigation Satellite System (GNSS) failure. The image matching system is based on edge detection in the aerial and geo-referenced image and posterior automatic image registration of these edge-images (position estimation of UAV). The edge detection process is performed by an Artificial Neural Network (ANN), with an optimal architecture. A comparison with Sobel and Canny edge extraction filters is also provided. The automatic image registration is obtained by a cross-correlation process. The ANN optimal architecture is set by the Multiple Particle Collision Algorithm (MPCA). The image matching system was implemented in a low cost/consumption portable computer. The image matching system has been tested on real flight-test data and encouraging results have been obtained. Results using real flight-test data will be presented.

[538] Full text  Jose Renato Garcia Braga, Gianpaolo Conte, Patrick Doherty, Haroldo Fraga Campos Velho and Elcio Hideiti Shiguemori. 2016.
Use of Artificial Neural Networks for Automatic Categorical Change Detection in Satellite Imagery.
In Proceedings of the 4th Conference of Computational Interdisciplinary Sciences (CCIS 2016). Pan American Association of Computational Interdisciplinary.

[537] Full text  Daniel de Leng and Fredrik Heintz. 2016.
DyKnow: A Dynamically Reconfigurable Stream Reasoning Framework as an Extension to the Robot Operating System.
In Proceedings of the Fifth IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), pages 55–60. IEEE conference proceedings. ISBN: 978-1-5090-4616-4, 978-1-5090-4617-1.
DOI: 10.1109/SIMPAR.2016.7862375.
Note: Funding agencies: National Graduate School in Computer Science, Sweden (CUGS); Swedish Foundation for Strategic Research (SSF) project CUAS; Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT Excellence Center at Linkoping- Lund for Information Technology; Swedis

DyKnow is a framework for stream reasoning aimed at robot applications that need to reason over a wide and varying array of sensor data for e.g. situation awareness. The framework extends the Robot Operating System (ROS). This paper presents the architecture and services behind DyKnow's run-time reconfiguration capabilities and offers an analysis of the quantitative and qualitative overhead. Run-time reconfiguration offers interesting advantages, such as fault recovery and the handling of changes to the set of computational and information resources that are available to a robot system. Reconfiguration capabilities are becoming increasingly important with the advances in areas such as the Internet of Things (IoT). We show the effectiveness of the suggested reconfiguration support by considering practical case studies alongside an empirical evaluation of the minimal overhead introduced when compared to standard ROS.

[536] Full text  Mehul Bhatt, Esra Erdem, Fredrik Heintz and Michael Spranger. 2016.
Cognitive robotics in JOURNAL OF EXPERIMENTAL and THEORETICAL ARTIFICIAL INTELLIGENCE, vol 28, issue 5, pp 779-780.
Journal of experimental and theoretical artificial intelligence (Print), 28(5):779–780. TAYLOR & FRANCIS LTD.
DOI: 10.1080/0952813X.2016.1218649.

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[535] Serge Thill, Alberto Montebelli and Tom Ziemke. 2016.
Workshop on Intention Recognition in HRI.
In 2016 11TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI), pages 585–586. In series: ACM/IEEE International Conference on Human-Robot Interaction #??. IEEE. ISBN: 978-1-4673-8370-7.
DOI: 10.1109/HRI.2016.7451868.

The present workshop focuses on the topic of intention recognition in HRI. To be able to recognise intentions of other agents is a fundamental prerequisite to engage in, for instance, instrumental helping or mutual collaboration. It is a necessary aspect of natural interaction. In HRI, the problem is therefore bi-directional: not only does a robot need the ability to infer intentions of humans; humans also need to infer the intentions of the robot. From the human perspective, this inference draws both on the ability to attribute cognitive states to lifeless shapes, and the ability to understand actions of other agents through, for instance, embodied processes or internal simulations (i.e the human ability to form a theory of mind of other agents). How precisely, and to what degree these mechanisms are at work when interacting with social artificial agents remains unknown. From the robotic perspective, this lack of understanding of mechanisms underlying human intention recognition, or the capacity for theory of mind in general, is also challenging: the solution can, for instance, not simply be to make autonomous systems work \"just like\" humans by copying the biological solution and implementing some technological equivalent. It is therefore important to be clear about the theoretical framework(s) and inherent assumptions underlying technological implementations related to mutual intention. This remains very much an active research area in which further development is necessary. The core purpose of this workshop is thus to contribute to and advance the state of the art in this area.

[534] Full text  Cyrille Berger, Piotr Rudol, Mariusz Wzorek and Alexander Kleiner. 2016.
Evaluation of Reactive Obstacle Avoidance Algorithms for a Quadcopter.
In Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision 2016 (ICARCV). In series: International Conference on Control Automation Robotics and Vision #??. IEEE conference proceedings. ISBN: 9781509035496, 9781509047574, 9781509035502.
DOI: 10.1109/ICARCV.2016.7838803.
Note: Funding agencies:This work is partially supported by the Swedish Research Council (VR) Linnaeus Center CADICS, the ELLIIT network organization for Information and Communication Technology, and the Swedish Foundation for Strategic Research (CUAS Project, SymbiKCIoud Project).

In this work we are investigating reactive avoidance techniques which can be used on board of a small quadcopter and which do not require absolute localisation. We propose a local map representation which can be updated with proprioceptive sensors. The local map is centred around the robot and uses spherical coordinates to represent a point cloud. The local map is updated using a depth sensor, the Inertial Measurement Unit and a registration algorithm. We propose an extension of the Dynamic Window Approach to compute a velocity vector based on the current local map. We propose to use an OctoMap structure to compute a 2-pass A* which provide a path which is converted to a velocity vector. Both approaches are reactive as they only make use of local information. The algorithms were evaluated in a simulator which offers a realistic environment, both in terms of control and sensors. The results obtained were also validated by running the algorithms on a real platform.

[533] Alexander Kleiner, Fredrik Heintz and Satoshi Tadokoro. 2016.
Editorial: Special Issue on Safety, Security, and Rescue Robotics (SSRR), Part 2.
Journal of Field Robotics, 33(4):409–410. WILEY-BLACKWELL.
DOI: 10.1002/rob.21661.

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[532] Full text  Tomas Melin. 2016.
Implementation and Evaluation of a Continuous Code Inspection Platform.
Student Thesis. 100 pages. ISRN: LIU-IDA/LITH-EX-A--16/047‚ÄĒSE.

Establishing and preserving a high level of software quality is a not a trivial task, although the benefits of succeeding with this task has been proven profitable and advantageous. An approach to mitigate the decreasing quality of a project is to track metrics and certain properties of the project, in order to view the progression of the project’s properties. This approach may be carried out by introducing continuous code inspection with the application of static code analysis. However, as the initial common opinion is that these type of tools produce a too high number of false positives, there is a need to investigate what the actual case is. This is the origin for the investigation and case study performed in this paper. The case study is performed at Ida Infront AB in Linköping, Sweden and involves interviews with developers to determine the performance of the continuous inspection platform SonarQube, in addition to examine the general opinion among developers at the company. The author executes the implementation and configuration of a continuous inspection environment to analyze a partition of the company’s product and determine what rules that are appropriate to apply in the company’s context. The results from the investigation indicate the high quality and accuracy of the tool, in addition to the advantageous functionality of continuously monitoring the code to observe trends and the progression of metrics such as cyclomatic complexity and duplicated code, with the goal of preventing the constant increase of complex and duplicated code. Combining this with features such as false positive suppression, instant analysis feedback in pull requests and the possibility to break the build given specified conditions, suggests that the implemented environment is a way to mitigate software quality difficulties.

[531] Full text  Patrick Doherty, Jonas KvarnstrŲm, Piotr Rudol, Mariusz Wzorek, Gianpaolo Conte, Cyrille Berger, Timo Hinzmann and Thomas Stastny. 2016.
A Collaborative Framework for 3D Mapping using Unmanned Aerial Vehicles.
In Baldoni, M., Chopra, A.K., Son, T.C., Hirayama, K., Torroni, P., editors, PRIMA 2016: Principles and Practice of Multi-Agent Systems, pages 110–130. In series: Lecture Notes in Computer Science #9862. Springer Publishing Company. ISBN: 978-3-319-44831-2.
DOI: 10.1007/978-3-319-44832-9_7.
Note: Accepted for publication.

This paper describes an overview of a generic framework for collaboration among humans and multiple heterogeneous robotic systems based on the use of a formal characterization of delegation as a speech act. The system used contains a complex set of integrated software modules that include delegation managers for each platform, a task specification language for characterizing distributed tasks, a task planner, a multi-agent scan trajectory generation and region partitioning module, and a system infrastructure used to distributively instantiate any number of robotic systems and user interfaces in a collaborative team. The application focusses on 3D reconstruction in alpine environments intended to be used by alpine rescue teams. Two complex UAV systems used in the experiments are described. A fully autonomous collaborative mission executed in the Italian Alps using the framework is also described.

[530] Full text  Martin Estgren. 2016.
Lightweight User Agents.
Student Thesis. 36 pages. ISRN: LIU-IDA/LITH-EX-G--16/036--SE.

The unit for information security and IT architecture at The Swedish Defence Research Agency (FOI) conducts work with a cyber range called CRATE (Cyber Range and Training Environment). Currently, simulation of user activity involves scripts inside the simulated network. This solution is not ideal because of the traces it leaves in the system and the general lack of standardised GUI API between different operating systems. FOI are interested in testing the use of artificial user agent located outside the virtual environment using computer vision and the virtualisation API to execute actions and extract information from the system.This paper focuses on analysing the reliability of template matching, a computer vision algorithm used to localise objects in images using already identified images of said object as templates. The analysis will evaluate both the reliability of localising objects and the algorithms ability to correctly identify if an object is present in the virtual environment.Analysis of template matching is performed by first creating a prototype of the agent's sensory system and then simulate scenarios which the agent might encounter. By simulating the environment, testing parameters can be manipulated and monitored in a reliable way. The parameters manipulated involves both the amount and type of image noise in the template and screenshot, the agent’s discrimination threshold for what constitutes a positive match, and information about the template such as template generality.This paper presents the performance and reliability of the agent in regards to what type of image noise affects the result, the amount of correctly identified objects given different discrimination thresholds, and computational time of template matching when different image filters are applied. Furthermore the best cases for each study are presented as comparison for the other results.In the end of the thesis we present how for screenshots with objects very similar to the templates used by the agent, template matching can result in a high degree of accuracy in both object localization and object identification and that a small reduction of similarity between template and screenshot to reduce the agent's ability to reliably identifying specific objects in the environment.

[529] Full text  Rasmus Holm. 2016.
Cluster Analysis of Discussions on Internet Forums.
Student Thesis. 62 pages. ISRN: LIU-IDA/LITH-EX-G--16/037‚ÄĒSE.

The growth of textual content on internet forums over the last decade have been immense which have resulted in users struggling to find relevant information in a convenient and quick way.The activity of finding information from large data collections is known as information retrieval and many tools and techniques have been developed to tackle common problems. Cluster analysis is a technique for grouping similar objects into smaller groups (clusters) such that the objects within a cluster are more similar than objects between clusters.We have investigated the clustering algorithms, Graclus and Non-Exhaustive Overlapping <em>k</em>-means (NEO-<em>k</em>-means), on textual data taken from Reddit, a social network service. One of the difficulties with the aforementioned algorithms is that both have an input parameter controlling how many clusters to find. We have used a greedy modularity maximization algorithm in order to estimate the number of clusters that exist in discussion threads.We have shown that it is possible to find subtopics within discussions and that in terms of execution time, Graclus has a clear advantage over NEO-<em>k</em>-means.

[528] Full text  Erik Hansson. 2016.
Search guidance with composite actions: Increasing the understandability of the domain model.
Student Thesis. 98 pages. ISRN: LIU-IDA/LITH-EX--16/043--SE.

This report presents an extension to the domain definition language for Threaded Forward-chaining Partial Order Planner (TFPOP) that can be used to increase the understandability of domain models. The extension consists of composite actions which is a method for expressing abstract actions as procedures of primitive actions. TFPOP can then uses these abstract actions when searching for a plan. An experiment, with students as participants, was used to show that using composite action can increase the understandability for non-expert users. Moreover, it was also proved the planner can utilize the composite action to significantly decrease the search time. Furthermore, indications was found that using composite actions is equally fast in terms of search time as using existing equivalent methods to decrease the search time.

[527] Full text  Anna Boyer de la Giroday. 2016.
Automatic fine tuning of cavity filters.
Student Thesis. 49 pages. ISRN: LIU-IDA/LITH-EX-A--16/036--SE.

Cavity filters are a necessary component in base stations used for telecommunication. Without these filters it would not be possible for base stations to send and receive signals at the same time. Today these cavity filters require fine tuning by humans before they can be deployed. This thesis have designed and implemented a neural network that can tune cavity filters. Different types of design parameters have been evaluated, such as neural network architecture, data presentation and data preprocessing. While the results was not comparable to human fine tuning, it was shown that there was a relationship between error and number of weights in the neural network. The thesis also presents some rules of thumb for future designs of neural network used for filter tuning.

[526] Alexander Kleiner, Fredrik Heintz and Satoshi Tadokoro. 2016.
Editorial: Special Issue on Safety, Security, and Rescue Robotics (SSRR), Part 1.
Journal of Field Robotics, 33(3):263–264. WILEY-BLACKWELL.
DOI: 10.1002/rob.21653.

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[525] Full text  Olov Andersson, Mariusz Wzorek, Piotr Rudol and Patrick Doherty. 2016.
Model-Predictive Control with Stochastic Collision Avoidance using Bayesian Policy Optimization.
In IEEE International Conference on Robotics and Automation (ICRA), 2016, pages 4597–4604. In series: Proceedings of IEEE International Conference on Robotics and Automation #??. Institute of Electrical and Electronics Engineers (IEEE).
DOI: 10.1109/ICRA.2016.7487661.

Robots are increasingly expected to move out of the controlled environment of research labs and into populated streets and workplaces. Collision avoidance in such cluttered and dynamic environments is of increasing importance as robots gain more autonomy. However, efficient avoidance is fundamentally difficult since computing safe trajectories may require considering both dynamics and uncertainty. While heuristics are often used in practice, we take a holistic stochastic trajectory optimization perspective that merges both collision avoidance and control. We examine dynamic obstacles moving without prior coordination, like pedestrians or vehicles. We find that common stochastic simplifications lead to poor approximations when obstacle behavior is difficult to predict. We instead compute efficient approximations by drawing upon techniques from machine learning. We propose to combine policy search with model-predictive control. This allows us to use recent fast constrained model-predictive control solvers, while gaining the stochastic properties of policy-based methods. We exploit recent advances in Bayesian optimization to efficiently solve the resulting probabilistically-constrained policy optimization problems. Finally, we present a real-time implementation of an obstacle avoiding controller for a quadcopter. We demonstrate the results in simulation as well as with real flight experiments.

[524] Full text  Daniel de Leng and Fredrik Heintz. 2016.
Qualitative Spatio-Temporal Stream Reasoning With Unobservable Intertemporal Spatial Relations Using Landmarks.
In Dale Schuurmans, Dale Wellman, editors, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pages 957–963. In series: Proceedings of the AAAI Conference on Artificial Intelligence #??. AAAI Press. ISBN: 978-1-57735-762-9.
Link to full text: http://www.aaai.org/ocs/index.php/AAAI/A...

Qualitative spatio-temporal reasoning is an active research area in Artificial Intelligence. In many situations there is a need to reason about intertemporal qualitative spatial relations, i.e. qualitative relations between spatial regions at different time-points. However, these relations can never be explicitly observed since they are between regions at different time-points. In applications where the qualitative spatial relations are partly acquired by for example a robotic system it is therefore necessary to infer these relations. This problem has, to the best of our knowledge, not been explicitly studied before. The contribution presented in this paper is two-fold. First, we present a spatio-temporal logic MSTL, which allows for spatio-temporal stream reasoning. Second, we define the concept of a landmark as a region that does not change between time-points and use these landmarks to infer qualitative spatio-temporal relations between non-landmark regions at different time-points. The qualitative spatial reasoning is done in RCC-8, but the approach is general and can be applied to any similar qualitative spatial formalism.

[523] Full text  Tommy Fšrnqvist, Fredrik Heintz, Patrick Lambrix, Linda Mannila and Chunyan Wang. 2016.
Supporting Active Learning by Introducing an Interactive Teaching Tool in a Data Structures and Algorithms Course.
In Proceedings of the 47th ACM Technical Symposium on Computer Science Education (SIGCSE 2016), pages 663–668. ACM Publications. ISBN: 978-1-4503-3685-7.
DOI: 10.1145/2839509.2844653.

Traditionally, theoretical foundations in data structures and algorithms (DSA) courses have been covered through lectures followed by tutorials, where students practise their understanding on pen-and-paper tasks. In this paper, we present findings from a pilot study on using the interactive e-book OpenDSA as the main material in a DSA course. The goal was to redesign an already existing course by building on active learning and continuous examination through the use of OpenDSA. In addition to presenting the study setting, we describe findings from four data sources: final exam, OpenDSA log data, pre and post questionnaires as well as an observation study. The results indicate that students performed better on the exam than during previous years. Students preferred OpenDSA over traditional textbooks and worked actively with the material, although a large proportion of them put off the work until the due date approaches.

[522] Full text  Mikael Nilsson, Jonas KvarnstrŲm and Patrick Doherty. 2016.
Efficient Processing of Simple Temporal Networks with Uncertainty: Algorithms for Dynamic Controllability Verification.
Acta Informatica, 53(6-8):723–752. Springer Publishing Company.
DOI: 10.1007/s00236-015-0248-8.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Temporal formalisms are essential for reasoning about actions that are carried out over time. The exact durations of such actions are generally hard to predict. In temporal planning, the resulting uncertainty is often worked around by only considering upper bounds on durations, with the assumption that when an action happens to be executed more quickly, the plan will still succeed. However, this assumption is often false: If we finish cooking too early, the dinner will be cold before everyone is ready to eat. Using <em>Simple Temporal Networks with Uncertainty (STNU)</em>, a planner can correctly take both lower and upper duration bounds into account. It must then verify that the plans it generates are executable regardless of the actual outcomes of the uncertain durations. This is captured by the property of <em>dynamic controllability</em> (DC), which should be verified incrementally during plan generation. Recently a new incremental algorithm for verifying dynamic controllability was proposed: <em>EfficiantIDC</em>, which can verify if an STNU that is DC remains DC after the addition or tightening of a constraint (corresponding to a new action being added to a plan). The algorithm was shown to have a worst case complexity of <em>O</em>(n<sup>4</sup>) for each addition or tightening. This can be amortized over the construction of a whole STNU for an amortized complexity in <em>O</em>(n<sup>3</sup>). In this paper we improve the <em>EfficientIDC</em> algorithm in a way that prevents it from having to reprocess nodes. This improvement leads to a lower worst case complexity in <em>O</em>(n<sup>3</sup>).

[521] Full text  HŚkan Warnquist, Jonas KvarnstrŲm and Patrick Doherty. 2016.
A Modeling Framework for Troubleshooting Automotive Systems.
Applied Artificial Intelligence, 30(3):257–296. Taylor & Francis.
DOI: 10.1080/08839514.2016.1156955.
Note: The published article is a shorter version than the version in manuscript form. The status of this article was earlier Manuscript.Funding agencies: Scania CV AB; FFI - Strategic Vehicle Research and Innovation; Excellence Center at Linkoping and Lund in Information Technology (ELLIIT); Research Council (VR) Linnaeus Center CADICS
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

This article presents a novel framework for modeling the troubleshooting process for automotive systems such as trucks and buses. We describe how a diagnostic model of the troubleshooting process can be created using event-driven, nonstationary, dynamic Bayesian networks. Exact inference in such a model is in general not practically possible. Therefore, we evaluate different approximate methods for inference based on the Boyen‚ÄďKoller algorithm. We identify relevant model classes that have particular structure such that inference can be made with linear time complexity. We also show how models created using expert knowledge can be tuned using statistical data. The proposed learning mechanism can use data that is collected from a heterogeneous fleet of modular vehicles that can consist of different components. The proposed framework is evaluated both theoretically and experimentally on an application example of a fuel injection system.

2015
[520] Fredrik LŲfgren, Jon Dybeck and Fredrik Heintz. 2015.
Qualification document: RoboCup 2015 Standard Platform League.
In , pages 1–2.
Qualification Video for RoboCup Standard Platform League 2015: https://www.youtube.com/watch?v=YNVzj6VL...
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

This is the application for the RoboCup 2015 StandardPlatform League from the ‚ÄĚLiU Robotics‚ÄĚ team. In thisdocument we present ourselves and what we want to achieve byour participation in the conference and competition

[519] Erik Sandewall. 2015.
Samtal om Sveriges nation.
Book. Volibri fŲrlag och IT. 154 pages. ISBN: 9789163792267.
Find book at a Swedish library/Hitta boken i ett svenskt bibliotek: http://libris.kb.se/hitlist?d=libris&q=9...

Demokratin ifrågasätts i dagens värld genom att auktoritära och fundamentalistiska ideologier av flera slag förs fram som alternativ. De tillämpas i praktiken i ett flertal länder, men de sprids också genom aktiv propaganda. Den här boken utgår från föreställningen att detta utgör en utmaning även för vårt land, och den föreslår framförallt två åtgärder för att möta den utmaningen.Ett förslag är att precisera samhällets demokratiska grundsatser och att komplettera dem med några ytterligare punkter, såsom följande. En princip om assimilationsfrihet formuleras, alltså en rättighet att byta etnisk, religiös eller politisk tillhörighet om man vill, och samtidigt förstås en rättighet att bevara den man har. I boken föreslås utvidgat skydd för dessa rättigheter. Likaså införs begreppet religionism, alltså hävdandet att en viss religion är överlägsen andra och är förutbestämd att ta över, och det föreslås att religionism ska likställas med rasism.Det andra huvudförslaget är att betrakta nationen som bäraren av detta utvidgade demokratibegrepp, men då handlar det om nationen i en annan bemärkelse än vad dagens `nationalister' föreställer sig. Boken anknyter till skillnaden mellan etnisk och samhällelig nationalism (`civic nationalism' på engelska). I den förra sökerman göra en etnisk grupp till en nation, i den senare ses nationen som fundamentet för staten och samhället, och som den samlande faktorn för alla medborgare som ansluter sig till det demokratiska samhällets principer.Boken hävdar också att en kunskap om Sveriges historia ur politisk och religiös synpunkt är viktig för att kunna relatera till de främmande ideologierna och för attförstå hur vår samhällsmodell förhåller sig till deras.

[518] Full text  Stefan Bršnd. 2015.
Using Rigid Landmarks to Infer Inter-Temporal Spatial Relations in Spatio-Temporal Reasoning.
Student Thesis. 32 pages. ISRN: LIU-IDA/LITH-EX-G--15/074--SE.

Spatio-temporal reasoning is the area of automated reasoning about space and time and is important in the field of robotics. It is desirable for an autonomous robot to have the ability to reason about both time and space. ST0 is a logic that allows for such reasoning by, among other things, defining a formalism used to describe the relationship between spatial regions and a calculus that allows for deducing further information regarding such spatial relations. An extension of ST0 is ST1 that can be used to describe the relationship between spatial entities across time-points (inter-temporal relations) while ST0 is constrained to doing so within a single time-point. This allows for a better ability of expressing how spatial entities change over time. A major obstacle in using ST1 in practise however, is the fact that any observations made regarding spatial relations between regions is constrained to the time-point in which the observation was made, so we are unable to observe inter-temporal relations. Further complicating things is the fact that deducing such inter-temporal relations is not possible without a frame of reference. This thesis examines one method of overcoming these problems by considering the concept of rigid regions which are assumed to always be unchanging and using them as the frame of reference, or as landmarks. The effectiveness of this method is studied by conducting experiments where a comparison is made between various landmark ratios with respect to the total number of regions under consideration. Results show that when a high degree of intra-temporal relations are fully or partially known, increasing the number of landmark regions will reduce the percentage of inter-temporal relations to be completely unknown. Despite this, very few inter-temporal relations can be fully determined even with a high ratio of landmark regions.

[517] Daniel de Leng. 2015.
Querying Flying Robots and Other Things: Ontology-supported stream reasoning.
, 22(2):44–47. Association for Computing Machinery (ACM).
Note: DOI does not work: 10.1145/2845155
Link to publication: http://xrds.acm.org/article.cfm?aid=2845...

A discussion on the role of ontologies and stream reasoning in Internet of Things applications.

[516] Full text  Valberg Joakim. 2015.
Document Separation in Digital Mailrooms.
Student Thesis. 47 pages. ISRN: LIU-IDA/LITH-EX-A-15/056-SE.

The growing mail volumes for businesses worldwide is one reason why theyare increasingly turning to digital mailrooms. A digital mailroom automaticallymanages the incoming mails, and a vital technology to its success isdocument classication. A problem with digital mailrooms and the documentclassication is separating the input stream of pages into documents.This thesis investigates existing classication theory and applies it to createan algorithm which solves the document separation problem. This algorithmis evaluated and compared against an existing algorithmic solution, over adataset containing real invoices.

[515] Full text  Tommy Fšrnqvist, Fredrik Heintz, Patrick Lambrix, Linda Mannila and Chunyan Wang. 2015.
Supporting Active Learning Using an Interactive Teaching Tool in a Data Structures and Algorithms Course.
In Proceedings of 5:e Utvecklingskonferensen fŲr Sveriges ingenjŲrsutbildningar (UtvSvIng), pages 76–79. In series: Technical report / Department of Information Technology, Uppsala University #2016-002.
Fulltext: http://utvecklingskonferens.it.uu.se/fil...

Traditionally, theoretical foundations in data structuresand algorithms (DSA) courses have been covered throughlectures followed by tutorials, where students practise theirunderstanding on pen-and-paper tasks. In this paper, we presentfindings from a pilot study on using the interactive e-bookOpenDSA as the main material in a DSA course. The goal was toredesign an already existing course by building on active learningand continuous examination through the use of OpenDSA. Inaddition to presenting the study setting, we describe findings fromfour data sources: final exam, OpenDSA log data, pre- and postcourse questionnaires as well as an observation study. The resultsindicate that students performed better on the exam than duringprevious years. Students preferred OpenDSA over traditionaltextbooks and worked actively with the material, although alarge proportion of them put off the work until the due dateapproaches.

[514] Full text  MichaŽl Grimsberg, Fredrik Heintz, Viggo Kann, Inger Erlander Klein and Lars ÷hrstrŲm. 2015.
Vem styr egentligen grundutbildningen?.
In Proceedings of 5:e Utvecklingskonferensen fŲr Sveriges ingenjŲrsutbildningar (UtvSvIng). In series: Technical report / Department of Information Technology, Uppsala University #2016-002.

Vi belyser olikheter och likheter i hur grundutbildningen styrs på fyra svenska tekniska högskolor. Vi jämför hur lärare och examinatorer väljs ut, hur medel fördelas och vilken roll programansvariga (eller motsvarande) har. De strukturella skillnaderna är relativt stora med störst autonomi för programansvariga på Chalmers tekniska högskola vilket delvis har att göra med att detta lärosäte lyder under aktiebolagslagen.

[513] Fredrik Heintz, Aseel Berglund, BjŲrn Hedin and Viggo Kann. 2015.
En jšmfŲrelse mellan programsamanhŚllande kurser vid KTH och LiU.
In Proceedings of 5:e Utvecklingskonferensen fŲr Sveriges ingenjŲrsutbildningar (UtvSvIng). In series: Technical report / Department of Information Technology, Uppsala University #2016-002.

Programsammanhållande kurser där studenter från årskurs 1-3 gemensamt reflekterar över teman med koppling till deras studier och framtida yrkesliv finns på både KTH och Linköpings universitet (LiU). Syftet med kurserna är främst att skapa en helhet i utbildningen och ge förståelse för vad den leder till, genom att få studenterna att reflektera över sina studier och sin kommande yrkesroll. Detta leder förhoppningsvis till ökad genomströmning och minskade avhopp. Kurserna har gemensamt ursprung men har utvecklats i olika riktningar. Artikeln jämför tre programsammanhållande kurser för Datateknik KTH, Medieteknik KTH samt Data- och mjukvaruteknik Linköpings universitet.

[512] Fredrik Heintz, Tommy Fšrnqvist and Jesper Thorťn. 2015.
Programutvecklingsstrategier fŲr att Ųka kopplingen mellan programmering och matematik.
In Proceedings of 5:e Utvecklingskonferensen fŲr Sveriges ingenjŲrsutbildningar (UtvSvIng). In series: Technical report / Department of Information Technology, Uppsala University #2016-002.

Matematik och programmering är två viktiga inslag i civilingenjörsprogram inom data- och mjukvaruteknik. De studenter som klarar dessa kurser klarar sannolikt resten av utbildningen. Idag har fler studenter programmering än matematik som huvudsakligt intresse. Därför har Linköpings universitet aktivt jobbat med olika strategier för att öka kopplingen mellan programmering och matematik, främst i de inledande kurserna. För att undersöka studenternas attityder till matematik och programmering har vi genomfört flera enkätstudier som bl.a. visar att intresset för matematik är stort men intresset för programmering ännu större och att studenterna tror de kommer ha betydligt mer nytta av programmering än matematik under sin karriär. Texten är tänkt som grund för en diskussion kring hur kopplingarna mellan matematik och programmering kan göras tydligare och starkare.

[511] Full text  Mikael Nilsson, Jonas KvarnstrŲm and Patrick Doherty. 2015.
Revisiting Classical Dynamic Controllability: A Tighter Complexity Analysis.
In B√©atrice Duval; Jaap van den Herik; Stephane Loiseau; Joaquim Filipe, editor, Agents and Artificial Intelligence: 6th International Conference, ICAART 2014, Angers, France, March 6?8, 2014, Revised Selected Papers, pages 243–261. In series: Lecture Notes in Computer Science #8946. Springer. ISBN: 978-3-319-25209-4, 978-3-319-25210-0.
DOI: 10.1007/978-3-319-25210-0_15.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essential to verify that such networks are dynamically controllable (DC) -- executable regardless of the outcomes of uncontrollable durations -- and to convert them to an executable form. We use insights from incremental DC verification algorithms to re-analyze the original, classical, verification algorithm. This algorithm is the entry level algorithm for DC verification, based on a less complex and more intuitive theory than subsequent algorithms. We show that with a small modification the algorithm is transformed from pseudo-polynomial to O(n<sup>4</sup>) which makes it still useful. We also discuss a change reducing the amount of work performed by the algorithm.

[510] Full text  HŚkan Warnquist. 2015.
Troubleshooting Trucks: Automated Planning and Diagnosis.
PhD Thesis. In series: LinkŲping Studies in Science and Technology. Dissertations #1691. LinkŲping University Electronic Press. 79 pages. ISBN: 978-91-7685-993-3.
DOI: 10.3384/diss.diva-119445.
cover: http://liu.diva-portal.org/smash/get/div...
preview image: http://liu.diva-portal.org/smash/get/div...

This thesis considers computer-assisted troubleshooting of heavy vehicles such as trucks and buses. In this setting, the person that is troubleshooting a vehicle problem is assisted by a computer that is capable of listing possible faults that can explain the problem and gives recommendations of which actions to take in order to solve the problem such that the expected cost of restoring the vehicle is low. To achieve this, such a system must be capable of solving two problems: the diagnosis problem of finding which the possible faults are and the decision problem of deciding which action should be taken.The diagnosis problem has been approached using Bayesian network models. Frameworks have been developed for the case when the vehicle is in the workshop only and for remote diagnosis when the vehicle is monitored during longer periods of time.The decision problem has been solved by creating planners that select actions such that the expected cost of repairing the vehicle is minimized. New methods, algorithms, and models have been developed for improving the performance of the planner.The theory developed has been evaluated on models of an auxiliary braking system, a fuel injection system, and an engine temperature control and monitoring system.

[509] Full text  Mattias Tiger and Fredrik Heintz. 2015.
Towards Unsupervised Learning, Classification and Prediction of Activities in a Stream-Based Framework.
In Proceedings of the Thirteenth Scandinavian Conference on Artificial Intelligence (SCAI), pages 147–156. In series: Frontiers in Artificial Intelligence and Applications #278. IOS Press. ISBN: 978-1-61499-588-3.
DOI: 10.3233/978-1-61499-589-0-147.
l√§nk till artikeln: https://www.ida.liu.se/divisions/aiics/p...

Learning to recognize common activities such as traffic activities and robot behavior is an important and challenging problem related both to AI and robotics. We propose an unsupervised approach that takes streams of observations of objects as input and learns a probabilistic representation of the observed spatio-temporal activities and their causal relations. The dynamics of the activities are modeled using sparse Gaussian processes and their causal relations using a probabilistic graph. The learned model supports in limited form both estimating the most likely current activity and predicting the most likely future activities. The framework is evaluated by learning activities in a simulated traffic monitoring application and by learning the flight patterns of an autonomous quadcopter.

[508] Full text  Daniel de Leng and Fredrik Heintz. 2015.
Ontology-Based Introspection in Support of Stream Reasoning.
In S. Nowaczyk, editor, Thirteenth scandinavian conference on artificial intelligence (SCAI), pages 78–87. IOS Press. ISBN: 9781614995883, 9781614995890.
Link to publication: https://www.ida.liu.se/divisions/aiics/p...

Building complex systems such as autonomous robots usually require the integration of a wide variety of components including high-level reasoning functionalities. One important challenge is integrating the information in a system by setting up the data flow between the components. This paper extends our earlier work on semantic matching with support for adaptive on-demand semantic information integration based on ontology-based introspection. We take two important standpoints. First, we consider streams of information, to handle the fact that information often becomes continually and incrementally available. Second, we explicitly represent the semantics of the components and the information that can be provided by them in an ontology. Based on the ontology our custom-made stream configuration planner automatically sets up the stream processing needed to generate the streams of information requested. Furthermore, subscribers are notified when properties of a stream changes, which allows them to adapt accordingly. Since the ontology represents both the systems information about the world and its internal stream processing many other powerful forms of introspection are also made possible. The proposed semantic matching functionality is part of the DyKnow stream reasoning framework and has been integrated in the Robot Operating System (ROS).

[507] Barbara Dunin-Keplicz and Andrzej Szalas. 2015.
A New Perspective on Goals.
In Sujata Ghosh and Jakub Szymanik, editors, The Facts Matter: Essays on Logic and Cognition in Honour of Rineke Verbrugge, pages 50–66. College Publications. ISBN: 978-1-84890-173-5.
Find book in another country/Hitta boken i ett annat land: http://www.worldcat.org/search?q=978-1-8...

This book is in celebration of Rineke Verbrugge's 50th birthday. It is a product of an incredible effort on the part of Rineke's teachers, colleagues, students and friends who have all been won over by her ever-encouraging and positive presence in academia and also in daily life. Pertaining to Rineke's research interests, the book features eight articles on a wide range of topics - from theories of arithmetic to a study on autism. The papers on hybrid logic, formal theories of belief, probability, goals, social networks, and bisimulations enrich the logic section of the book while papers on cognitive strategizing and social cognition bring up the cognitive perspective. The themes themselves provide a compelling perception of the vast expanse of Rineke's academic interests and endeavours. A series of personal comments, stories, anecdotes, and pictures constitute the latter part of the book, adding a distinct personal touch to this volume.

[506] Full text  Mikael Nilsson. 2015.
Efficient Temporal Reasoning with Uncertainty.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1722. LinkŲping University Electronic Press. 116 pages. ISBN: 9789176859919.
DOI: 10.3384/lic.diva-119409.
cover: http://liu.diva-portal.org/smash/get/div...
preview image: http://liu.diva-portal.org/smash/get/div...

Automated Planning is an active area within Artificial Intelligence. With the help of computers we can quickly find good plans in complicated problem domains, such as planning for search and rescue after a natural disaster. When planning in realistic domains the exact duration of an action generally cannot be predicted in advance. Temporal planning therefore tends to use upper bounds on durations, with the explicit or implicit assumption that if an action happens to be executed more quickly, the plan will still succeed. However, this assumption is often false. If we finish cooking <em>too early</em>, the dinner will be cold before everyone is at home and can eat. Simple Temporal Networks with Uncertainty (STNUs) allow us to model such situations. An STNU-based planner must verify that the temporal problems it generates are executable, which is captured by the property of <em>dynamic controllability</em> (DC). If a plan is not dynamically controllable, adding actions cannot restore controllability. Therefore a planner should verify after each action addition whether the plan remains DC, and if not, backtrack. Verifying dynamic controllability of a full STNU is computationally intensive. Therefore, <em>incremental</em> DC verification algorithms are needed.We start by discussing two existing algorithms relevant to the thesis. These are the very first DC verification algorithm called MMV (by <strong>M</strong>orris, <strong>M</strong>uscettola and <strong>V</strong>idal) and the <em>incremental DC</em> verification algorithm called FastIDC, which is based on MMV.We then show that FastIDC is not sound, sometimes labeling networks as dynamically controllable when they are not. We analyze the algorithm to pinpoint the cause and show how the algorithm can be modified to correctly and efficiently detect uncontrollable networks.In the next part we use insights from this work to re-analyze the MMV algorithm. This algorithm is pseudo-polynomial and was later subsumed by first an n<sup>5</sup> algorithm and then an n<sup>4</sup> algorithm. We show that the basic techniques used by MMV can in fact be used to create an n<sup>4</sup> algorithm for verifying dynamic controllability, with a new termination criterion based on a deeper analysis of MMV. This means that there is now a comparatively easy way of implementing a highly efficient dynamic controllability verification algorithm. From a theoretical viewpoint, understanding MMV is important since it acts as a building block for all subsequent algorithms that verify dynamic controllability. In our analysis we also discuss a change in MMV which reduces the amount of regression needed in the network substantially.In the final part of the thesis we show that the FastIDC method can result in traversing part of a temporal network multiple times, with constraints slowly tightening towards their final values. As a result of our analysis we then present a new algorithm with an improved traversal strategy that avoids this behavior. The new algorithm, EfficientIDC, has a time complexity which is lower than that of FastIDC. We prove that it is sound and complete.

[505] Linh Anh Nguyen, Thi-Bich-Loc Nguyen and Andrzej Szalas. 2015.
Towards richer rule languages with polynomial data complexity for the Semantic Web.
Data & Knowledge Engineering, 96-97(??):57–77. ELSEVIER SCIENCE BV.
DOI: 10.1016/j.datak.2015.04.005.

We introduce a Horn description logic called Horn-DL, which is strictly and essentially richer than Horn-Reg(1), Horn-SHTQ and Horn-SROIQ, while still has PTime data complexity. In comparison with Horn-SROIQ, Horn-DL additionally allows the universal role and assertions of the form irreflexive(s), -s(a, b), a b. More importantly, in contrast to all the well-known Horn fragments epsilon L, DL-Lite, DLP, Horn-SHIQ, and Horn-SROIQ of description logics, Horn-DL allows a form of the concept constructor \"universal restriction\" to appear at the left hand side of terminological inclusion axioms. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. We develop the first algorithm with PTime data complexity for checking satisfiability of Horn-DL knowledge bases.

[504] Full text  Daniel de Leng and Fredrik Heintz. 2015.
Ontology-Based Introspection in Support of Stream Reasoning.
In Odile Papini, Salem Benferhat, Laurent Garcia, Marie-Laure Mugnier, Eduardo Ferm√©, Thomas Meyer, Renata Wassermann, Torsten Hahmann, Ken Baclawski, Adila Krisnadhi, Pavel Klinov, Stefano Borgo and Oliver Kutz Daniele Porello15, editors, Proceedings of the Joint Ontology Workshops (JOWO 2015), Buenos Aires, Argentina, July 25-27, 2015: The Joint Ontology Workshops - Episode 1, pages 1–8. In series: CEUR Workshop Proceedings #??. Rheinisch-Westfaelische Technische Hochschule Aachen * Lehrstuhl Informatik V.
Note: Workshops held at the 24th International Joint Conference on Artificial Intelligence - IJCAI 2015, Buenos Aires, Argentina, July 25-27, 2015
Link to publication: http://ceur-ws.org/Vol-1517/JOWO-15_FOfA...
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Building complex systems such as autonomous robots usually require the integration of a wide variety of components including high-level reasoning functionalities. One important challenge is integrating the information in a system by setting up the data flow between the components. This paper extends our earlier work on semantic matching with support for adaptive on-demand semantic information integration based on ontology-based introspection. We take two important stand-points. First, we consider streams of information, to handle the fact that information often becomes continually and incrementally available. Second, we explicitly represent the semantics of the components and the information that can be provided by them in an ontology. Based on the ontology our custom-made stream configuration planner automatically sets up the stream processing needed to generate the streams of information requested. Furthermore, subscribers are notified when properties of a stream changes, which allows them to adapt accordingly. Since the ontology represents both the system's information about the world and its internal stream processing many other powerful forms of introspection are also made possible. The proposed semantic matching functionality is part of the DyKnow stream reasoning framework and has been integrated in the Robot Operating System (ROS).

[503] Full text  Erik SommarstrŲm. 2015.
I am the Greatest Driver in the World!: -Does self-awareness of driving ability affect traffic safety behaviour?.
Student Thesis. 43 pages. ISRN: LIU-IDA/KOGVET-A--15/008‚ÄĒSE.

This simulator study aims to investigate if there is a relationship between self-awareness of driving ability and traffic safety behaviour. Self-awareness in this study is accurate self-evaluation of one‚Äôs abilities. By letting 97 participants (55-75 years old) drive the simulator and answering the Driver Skill Inventory (DSI; Warner et al., 2013) as well as the Multidimensional locus of control (T-loc; √Ėzkan &amp; Lajunen, 2005). A measure of self-awareness was computed using the residuals from regression line. Furthermore, this measure could show if a participant over-estimated or under-estimated their ability. Four self-awareness measures were made. The self-awareness measures were compared to traffic safety behaviour. Three different traffic safety measures were computed using specific events in the simulator scenario. The self-awareness measures were grouped into three groups; under-estimators, good self-awareness and over-estimators. These groups were then compared to each other with respect to traffic safety. A multivariate ANOVA was made to test for differences between the self-awareness groups but no significant main difference was found. The results showed no difference in traffic safety behaviour given the different levels of self-awareness. Furthermore, this could be a result of the old age of the sample group as self-awareness may only be relevant in a learning context. The conclusion of the study is that the analysis shows that there is no difference between over-estimators and under-estimators of driving ability, at least not in experienced older drivers.

[502] Tina Danielsson. 2015.
Portering frŚn Google Apps REST API till Microsoft Office 365 REST API.
Student Thesis. 10 pages. ISRN: LiTH-IDA/ERASMUS-G--15/003--SE.

Stress på arbetsplatsen relaterat till många inkommande och utgående kommunikationskanaler är ett reellt problem. Applikationer som samlar alla kanaler i samma verktyg kan hjälpa till på det här området. För att förenkla vid utveckling av en sådan applikation kan ett modulärt system skapas, där varje modul ser liknande ut och enkelt kan kopplas in i en huvudapplikation. Den här studien undersöker de problem som kan uppstå när flera tjänster ska integreras, mer specifikt genom att titta på hur en befintlig modul för e-post via Google Apps kan porteras för att stödja e-post via Microsoft Office 365. Arbetet har skett enligt metoder för testdriven portering och varje steg i porteringen har dokumenterats noggrant. Ett antal problemområden har identifierats och möjliga lösningar föreslås. Utfrån de problem som uppstått dras slutsatsen att de är av en sådan karaktär att de inte utgör något hinder för en portering.

[501] Full text  Jonas Hietala. 2015.
A Comparison of Katz-eig and Link-analysis for Implicit Feedback Recommender Systems.
Student Thesis. 85 pages. ISRN: LIU-IDA/LITH-EX-A--15/026--SE.

Link: http://www.jonashietala.se/masters_thesi...

Recommendations are becoming more and more important in a world where there is an abundance of possible choices and e-commerce and content providers are featuring recommendations prominently. Recommendations based on explicit feedback, where user is giving feedback for example with ratings, has been a popular research subject. Implicit feedback recommender systems which passively collects information about the users is an area growing in interest. It makes it possible to generate recommendations based purely from a user's interactions history without requiring any explicit input from the users, which is commercially useful for a wide area of businesses. This thesis builds a recommender system based on implicit feedback using the recommendation algorithms katz-eig and link-analysis and analyzes and implements strategies for learning optimized parameters for different datasets. The resulting system forms the foundation for Comordo Technologies' commercial recommender system.

[500] Full text  Fredrik Heintz, Linda Mannila, Karin NygŚrds, Peter Parnes and BjŲrn Regnell. 2015.
Computing at School in Sweden ? Experiences fromIntroducing Computer Science within Existing Subjects.
In Proceeding of the 8th International Conference on Informatics in Schools:Situation, Evolution, and Perspective (ISSEP). In series: Lecture Notes in Computer Science #9378. Springer. ISBN: 978-3-319-25395-4.

Computing is no longer considered a subject area only relevant for anarrow group of professionals, but rather as a vital part of general education thatshould be available to all children and youth. Since making changes to nationalcurricula takes time, people are trying to find other ways of introducing childrenand youth to computing. In Sweden, several current initiatives by researchers andteachers aim at finding ways of working with computing within the current curriculum.In this paper we present case studies based on a selection of these initiativesfrom four major regions in Sweden and based on these case studies wepresent our ideas for how to move forward on introducing computational thinkingon a larger scale in Swedish education.

[499] Full text  Mattias Tiger and Fredrik Heintz. 2015.
Online Sparse Gaussian Process Regression for Trajectory Modeling.
In 18th International Conference on Information Fusion (Fusion), 2015, pages 782–791. IEEE. ISBN: 9780982443866, 9780982443873.
Publisher's full text: https://ieeexplore.ieee.org/document/726...

Trajectories are used in many target tracking and other fusion-related applications. In this paper we consider the problem of modeling trajectories as Gaussian processes and learning such models from sets of observed trajectories. We demonstrate that the traditional approach to Gaussian process regression is not suitable when modeling a set of trajectories. Instead we introduce an approach to Gaussian process trajectory regression based on an alternative way of combing two Gaussian process (GP) trajectory models and inverse GP regression. The benefit of our approach is that it works well online and efficiently supports sophisticated trajectory model manipulations such as merging and splitting of trajectory models. Splitting and merging is very useful in spatio-temporal activity modeling and learning where trajectory models are considered discrete objects. The presented method and accompanying approximation algorithm have time and memory complexities comparable to state of the art of regular full and approximative GP regression, while havinga more flexible model suitable for modeling trajectories. The novelty of our approach is in the very flexible and accurate model, especially for trajectories, and the proposed approximative method based on solving the inverse problem of Gaussian process regression.

[498] Full text  Patrik BergstrŲm. 2015.
Automated Setup of Display Protocols.
Student Thesis. 44 pages. ISRN: LIU-IDA/LITH-EX-A--15/014--SE.

Link: http://urn.kb.se/resolve?urn=urn:nbn:se:...

Radiologists' workload has been steadily increasing for decades. As digital technology matures it improves the workflow for radiology departments and decreases the time necessary to examine patients. Computer systems are widely used in health care and are for example used to view radiology images. To simplify this, display protocols based on examination data are used to automatically create a layout and hang images for the user. To cover a wide variety of examinations hundreds of protocols must be created, which is a time-consuming task and the system can still fail to hang series if strict requirements on the protocols are not met. To remove the need for this manual step we propose to use machine learning based on past manually corrected presentations. The classifiers are trained on the metadata in the examination and how the radiologist preferred to hang the series. The chosen approach was to create classifiers for different layout rules and then use these predictions in an algorithm for assigning series types to individual image slots according to categories based on metadata, similar to how display protocol works. The resulting presentations shows that the system is able to learn, but must increase its prediction accuracy if it is to be used commercially. Analyses of the different parts show that increased accuracy in early steps should improve overall success.

[497] Full text  Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg, Karl GranstrŲm, Fredrik Heintz, Piotr Rudol, Mariusz Wzorek, Jonas KvarnstrŲm and Patrick Doherty. 2015.
A Low-Level Active Vision Framework for Collaborative Unmanned Aircraft Systems.
In Lourdes Agapito, Michael M. Bronstein and Carsten Rother, editors, COMPUTER VISION - ECCV 2014 WORKSHOPS, PT I, pages 223–237. In series: Lecture Notes in Computer Science #8925. Springer Publishing Company. ISBN: 978-3-319-16177-8, 978-3-319-16178-5.
DOI: 10.1007/978-3-319-16178-5_15.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Micro unmanned aerial vehicles are becoming increasingly interesting for aiding and collaborating with human agents in myriads of applications, but in particular they are useful for monitoring inaccessible or dangerous areas. In order to interact with and monitor humans, these systems need robust and real-time computer vision subsystems that allow to detect and follow persons.In this work, we propose a low-level active vision framework to accomplish these challenging tasks. Based on the LinkQuad platform, we present a system study that implements the detection and tracking of people under fully autonomous flight conditions, keeping the vehicle within a certain distance of a person. The framework integrates state-of-the-art methods from visual detection and tracking, Bayesian filtering, and AI-based control. The results from our experiments clearly suggest that the proposed framework performs real-time detection and tracking of persons in complex scenarios

[496] Full text  Karl Nygren. 2015.
Trust Logics and Their Horn Fragments: Formalizing Socio-Cognitive Aspects of Trust.
Student Thesis. 93 pages. ISRN: LiTH-MAT-EX--2015/01--SE.

This thesis investigates logical formalizations of Castelfranchi and Falcone's (C&amp;F) theory of trust [9, 10, 11, 12]. The C&amp;F theory of trust defines trust as an essentially mental notion, making the theory particularly well suited for formalizations in multi-modal logics of beliefs, goals, intentions, actions, and time.Three different multi-modal logical formalisms intended for multi-agent systems are compared and evaluated along two lines of inquiry. First, I propose formal definitions of key concepts of the C&amp;F theory of trust and prove some important properties of these definitions. The proven properties are then compared to the informal characterisation of the C&amp;F theory. Second, the logics are used to formalize a case study involving an Internet forum, and their performances in the case study constitute grounds for a comparison. The comparison indicates that an accurate modelling of time, and the interaction of time and goals in particular, is integral for formal reasoning about trust.Finally, I propose a Horn fragment of the logic of Herzig, Lorini, Hubner, and Vercouter [25]. The Horn fragment is shown to be too restrictive to accurately express the considered case study.

[495] Barbara Dunin-Keplicz, Alina Strachocka, Andrzej Szalas and Rineke Verbrugge. 2015.
Paraconsistent semantics of speech acts.
Neurocomputing, 151(2):943–952. Elsevier.
DOI: 10.1016/j.neucom.2014.10.001.

This paper discusses an implementation of four speech acts: assert, concede, request and challenge in a paraconsistent framework. A natural four-valued model of interaction yields multiple new cognitive situations. They are analyzed in the context of communicative relations, which partially replace the concept of trust. These assumptions naturally lead to six types of situations, which often require performing conflict resolution and belief revision. The particular choice of a rule-based, DATALOC. like query language 4QL as a four-valued implementation framework ensures that, in contrast to the standard two-valued approaches, tractability of the model is achieved.

[494] Full text  Patrick Doherty and Andrzej Szalas. 2015.
Stability, Supportedness, Minimality and Kleene Answer Set Programs.
In Thomas Eiter, Hannes Strass, MirosŇāaw Truszczynski, Stefan Woltran, editors, Advances in Knowledge Representation, Logic Programming, and Abstract Argumentation: Essays Dedicated to Gerhard Brewka on the Occasion of His 60th Birthday, pages 125–140. In series: Lecture Notes in Computer Science #9060. Springer. ISBN: 978-3-319-14725-3, 978-3-319-14726-0.
DOI: 10.1007/978-3-319-14726-0_9.
Link to full text: http://www.ida.liu.se/divisions/aiics/pu...
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Answer Set Programming is a widely known knowledge representation framework based on the logic programming paradigm that has been extensively studied in the past decades. The semantic framework for Answer Set Programs is based on the use of stable model semantics. There are two characteristics intrinsically associated with the construction of stable models for answer set programs. Any member of an answer set is supported through facts and chains of rules and those members are in the answer set only if generated minimally in such a manner. These two characteristics, supportedness and minimality, provide the essence of stable models. Additionally, answer sets are implicitly partial and that partiality provides epistemic overtones to the interpretation of disjunctiver ules and default negation. This paper is intended to shed light on these characteristics by defining a semantic framework for answer set programming based on an extended first-order Kleene logic with weak and strong negation. Additionally, a definition of strongly supported models is introduced, separate from the minimality assumption explicit in stable models. This is used to both clarify and generate alternative semantic interpretations for answer set programs with disjunctive rules in addition to answer set programs with constraint rules. An algorithm is provided for computing supported models and comparative complexity results between strongly supported and stable model generation are provided.

[493] Full text  Olov Andersson, Fredrik Heintz and Patrick Doherty. 2015.
Model-Based Reinforcement Learning in Continuous Environments Using Real-Time Constrained Optimization.
In Blai Bonet and Sven Koenig, editors, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), pages 2497–2503. AAAI Press. ISBN: 978-1-57735-698-1.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Reinforcement learning for robot control tasks in continuous environments is a challenging problem due to the dimensionality of the state and action spaces, time and resource costs for learning with a real robot as well as constraints imposed for its safe operation. In this paper we propose a model-based reinforcement learning approach for continuous environments with constraints. The approach combines model-based reinforcement learning with recent advances in approximate optimal control. This results in a bounded-rationality agent that makes decisions in real-time by efficiently solving a sequence of constrained optimization problems on learned sparse Gaussian process models. Such a combination has several advantages. No high-dimensional policy needs to be computed or stored while the learning problem often reduces to a set of lower-dimensional models of the dynamics. In addition, hard constraints can easily be included and objectives can also be changed in real-time to allow for multiple or dynamic tasks. The efficacy of the approach is demonstrated on both an extended cart pole domain and a challenging quadcopter navigation task using real data.

2014
[492] HŚkan Warnquist, Mattias Nyberg and Jonas Biteus. 2014.
Guided Integrated Remote and Workshop Troubleshooting of Heavy Trucks.
International Journal of Commercial Vehicles, 7(1):25–36. SAE International.
DOI: 10.4271/2014-01-0284.

When a truck or bus suffers from a breakdown it is important that the vehicle comes back on the road as soon as possible. In this paper we present a prototype diagnostic decision support system capable of automatically identifying possible causes of a failure and propose recommended actions on how to get the vehicle back on the road as cost efficiently as possible.This troubleshooting system is novel in the way it integrates the remote diagnosis with the workshop diagnosis when providing recommendations. To achieve this integration, a novel planning algorithm has been developed that enables the troubleshooting system to guide the different users (driver, help-desk operator, and mechanic) through the entire troubleshooting process.In this paper we formulate the problem of integrated remote and workshop troubleshooting and present a working prototype that has been implemented to demonstrate all parts of the troubleshooting system.

[491] Linh Anh Nguyen, Thi-Bich-Loc Nguyen and Andrzej Szalas. 2014.
A Horn Fragment with PTime Data Complexity of Regular Description Logic with Inverse.
VNU Journal of Computer Science and Communication Engineering, 30(4):14–28.
Link to publication: http://www.jcsce.vnu.edu.vn/index.php/jc...

We study a Horn fragment called Horn-RegI of the regular description logic with inverse RegI, which extends the description logic ALC with inverse roles and regular role inclusion axioms characterized by finite automata. In contrast to the well-known Horn fragments EL, DL-Lite, DLP, Horn-SHIQ and Horn-SROIQ of description logics, Horn-RegI allows a form of the concept constructor \"universal restriction\" to appear at the left hand side of terminological inclusion axioms, while still has PTIME data complexity. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. We provide an algorithm with PTIME data complexity for checking satisfiability of Horn-RegI knowledge bases.

[490] Lukasz Bialek and Andrzej Szalas. 2014.
Lightweight Reasoning with Incomplete and Inconsistent Information: a Case Study.
In 2014 IEEE/WIC/ACM International Joint Conferences on †(Volume:3 ) Web Intelligence (WI) and Intelligent Agent Technologies (IAT),, pages 325–332. IEEE. ISBN: 978-1-4799-4143-8.
DOI: 10.1109/WI-IAT.2014.184.

Dealing with heterogeneous information sources and reasoning techniques allowing for incomplete and inconsistent information is one of current challenges in the area of knowledge representation and reasoning. We advocate for 4QL, a rule-based query language, as a proper tool allowing one to address these challenges. To justify this point of view we discuss a rescue robotics scenario for which a simulator has been developed and tested. In particular, we present a planner using 4QL and, therefore, capable to deal with lack of knowledge and inconsistencies. Through the case study we show that our approach allows one to use lightweight knowledge representation tools: due to the use of 4QL tractability of modeling and reasoning is guaranteed and high usability is achieved.

[489] Barbara Dunin-Keplicz and Andrzej Szalas. 2014.
Indeterministic Belief Structures.
In Agent and Multi-Agent Systems: Technologies and Applications: Proceedings of the 8th International Conference KES-AMSTA 2014, Chania, Greece, June 2014, pages 57–66. In series: Advances in Intelligent Systems and Computing #296. Springer International Publishing. ISBN: 978-3-319-07649-2, 978-3-319-07650-8.
DOI: 10.1007/978-3-319-07650-8_7.

The current paper falls into a bigger research programme concerning construction of modern belief structures applicable in multiagent systems. In previous papers we approached individual and group beliefs via querying paraconsistent belief bases. This framework, covering deterministic belief structures, turned out to be tractable under some natural restrictions on implementation. Moreover, we have indicated a four-valued query language 4QL as an implementation tool guaranteeing tractability and capturing all PTime -constructible belief structures.In this paper we generalize our approach to the nondeterministic case. This is achieved by adjusting the key abstractions of epistemic profiles and belief structures to this new situation. Importantly, tractability of the approach is still maintained.

[488] Barbara Dunin-Keplicz, Andrzej Szalas and Rineke Verbrugge. 2014.
Tractable Reasoning about Group Beliefs.
In ENGINEERING MULTI-AGENT SYSTEMS, EMAS 2014, pages 328–350. In series: Lecture Notes in Computer Science #8758. SPRINGER INT PUBLISHING AG. ISBN: 978-3-319-14484-9, 978-3-319-14483-2.
DOI: 10.1007/978-3-319-14484-9_17.

In contemporary autonomous systems, like robotics, the need to apply group knowledge has been growing consistently with the increasing complexity of applications, especially those involving teamwork. However, classical notions of common knowledge and common belief, as well as their weaker versions, are too complex. Also, when modeling real-world situations, lack of knowledge and inconsistency of information naturally appear. Therefore, we propose a shift in perspective from reasoning in multi-modal logics to querying paraconsistent knowledge bases. This opens the possibility for exploring a new approach to group beliefs. To demonstrate expressiveness of our approach, examples of social procedures leading to complex belief structures are constructed via the use of epistemic profiles. To achieve tractability without compromising the expressiveness, as an implementation tool we choose 4QL, a four-valued rule-based query language. This permits both to tame inconsistency in individual and group beliefs and to execute the social procedures in polynomial time. Therefore, a marked improvement in efficiency has been achieved over systems such as (dynamic) epistemic logics with common knowledge and ATL, for which problems like model checking and satisfiability are PSPACE- or even EXPTIME-hard.

[487] Full text  Aseel Berglund and Fredrik Heintz. 2014.
Integrating Soft Skills into Engineering Education for Increased Student Throughput and more Professional Engineers.
In Proceedings of LTHs 8:e Pedagogiska Inspirationskonferens (PIK). Lunds university.
Link to publication: http://www.lth.se/fileadmin/lth/genombro...

Soft skills are recognized as crucial for engineers as technical work is becoming more and more collaborative and interdisciplinary. Today many engineering educations fail to give appropriate training in soft skills. Link√∂ping University has therefore developed a completely new course ‚ÄúProfessionalism for Engineers‚ÄĚ for two of its 5-year engineering programs in the area of computer science. The course stretches over the first 3 years with students from the three years taking it together. The purpose of the course is to give engineering students training in soft skills that are of importance during the engineering education as well as during their professional career. The examination is based on the Dialogue Seminar Method developed for learning from experience and through reflection. The organization of the course is innovative in many ways.

[486] Full text  Alexander Bock, Alexander Kleiner, Jonas Lundberg and Timo Ropinski. 2014.
Supporting Urban Search & Rescue Mission Planning through Visualization-Based Analysis.
In Proceedings of the Vision, Modeling, and Visualization Conference 2014. Eurographics - European Association for Computer Graphics. ISBN: 978-3-905674-74-3.
DOI: 10.2312/vmv.20141275.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

We propose a visualization system for incident commanders in urban search~\&amp;~rescue scenarios that supports access path planning for post-disaster structures. Utilizing point cloud data acquired from unmanned robots, we provide methods for assessment of automatically generated paths. As data uncertainty and a priori unknown information make fully automated systems impractical, we present a set of viable access paths, based on varying risk factors, in a 3D environment combined with the visual analysis tools enabling informed decisions and trade-offs. Based on these decisions, a responder is guided along the path by the incident commander, who can interactively annotate and reevaluate the acquired point cloud to react to the dynamics of the situation. We describe design considerations for our system, technical realizations, and discuss the results of an expert evaluation.

[485] S.T. Cao, L.A. Nguyen and Andrzej Szalas. 2014.
The web ontology rule language OWL 2 RL+ and its extensions.
In Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen, editors, Transactions on Computational Collective Intelligence XIII, pages 152–175. In series: Lecture Notes in Computer Science #8342. Springer Verlag (Germany). ISBN: 978-3-642-54454-5.
DOI: 10.1007/978-3-642-54455-2_7.

It is known that the OWL 2RL Web Ontology Language Profile has PTime data complexity and can be translated into Datalog. However, the result of translation may consist of a Datalog program and a set of constraints in the form of negative clauses. Therefore, a knowledge base in OWL 2RL may be unsatisfiable. In the current paper we first identify a maximal fragment of OWL 2RL, called OWL 2RL+, with the property that every knowledge base expressed in OWL2RL+ can be translated to a Datalog program and hence is satisfiable. We then propose some extensions of OWL 2RL and OWL 2RL + that still have PTime data complexity. © 2014 Springer-Verlag Berlin Heidelberg.

[484] Andrzej Szalas. 2014.
Symbolic Explanations of Generalized Fuzzy Reasoning.
In SMART DIGITAL FUTURES 2014, pages 7–16. In series: Frontiers in Artificial Intelligence and Applications #??. IOS Press. ISBN: 978-1-61499-405-3; 978-1-61499-404-6.
DOI: 10.3233/978-1-61499-405-3-7.

Various generalizations of fuzzy reasoning are frequently used in decision making. While in many application areas it is natural to assume that truth degrees of a property and its complement sum up to 1, such an assumption appears problematic, e.g., in modeling ignorance. Therefore, in some generalizations of fuzzy sets, degrees of membership in a set and in its complement are separated and are no longer required to sum up to 1. In frequent cases, this separation of positive and negative evidences for concept membership is more natural. As we discuss in the current paper, symbolic explanations of results of such forms of reasoning provide additional important information. In the present paper we address two related questions: (i) given generalized fuzzy connectives and a finite set of truth values T, find a finitely-valued logic over T, explaining fuzzy reasoning, and (ii) given a finitely-valued logic, find a fuzzy semantics, explained by the given logic. We also show examples illustrating usefulness of the approach.

[483] Full text  Patrick Doherty, Jonas KvarnstrŲm, Mariusz Wzorek, Piotr Rudol, Fredrik Heintz and Gianpaolo Conte. 2014.
HDRC3 - A Distributed Hybrid Deliberative/Reactive Architecture for Unmanned Aircraft Systems.
In Kimon P. Valavanis, George J. Vachtsevanos, editors, Handbook of Unmanned Aerial Vehicles, pages 849–952. Springer Science+Business Media B.V.. ISBN: 978-90-481-9706-4, 978-90-481-9707-1.
DOI: 10.1007/978-90-481-9707-1_118.
Find book at a Swedish library/Hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/16541662
Find book in another country/Hitta boken i ett annat land: http://www.worldcat.org/search?qt=worldc...

This chapter presents a distributed architecture for unmanned aircraft systems that provides full integration of both low autonomy and high autonomy. The architecture has been instantiated and used in a rotorbased aerial vehicle, but is not limited to use in particular aircraft systems. Various generic functionalities essential to the integration of both low autonomy and high autonomy in a single system are isolated and described. The architecture has also been extended for use with multi-platform systems. The chapter covers the full spectrum of functionalities required for operation in missions requiring high autonomy. A control kernel is presented with diverse flight modes integrated with a navigation subsystem. Specific interfaces and languages are introduced which provide seamless transition between deliberative and reactive capability and reactive and control capability. Hierarchical Concurrent State Machines are introduced as a real-time mechanism for specifying and executing low-level reactive control. Task Specification Trees are introduced as both a declarative and procedural mechanism for specification of high-level tasks. Task planners and motion planners are described which are tightly integrated into the architecture. Generic middleware capability for specifying data and knowledge flow within the architecture based on a stream abstraction is also described. The use of temporal logic is prevalent and is used both as a specification language and as an integral part of an execution monitoring mechanism. Emphasis is placed on the robust integration and interaction between these diverse functionalities using a principled architectural framework. The architecture has been empirically tested in several complex missions, some of which are described in the chapter.

[482] Full text  Cyrille Berger. 2014.
Strokes detection for skeletonisation of characters shapes.
In George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Chandra Kambhamettu, Maha El Choubassi, Zhigang Deng, Mark Carlson, editors, Advances in Visual Computing: 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings, Part II, pages 510–520. In series: Lecture Notes in Computer Science #8888. Springer. ISBN: 978-3-319-14364-4, 978-3-319-14363-7.
DOI: 10.1007/978-3-319-14364-4_49.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Skeletonisation is a key process in character recognition in natural images. Under the assumption that a character is made of a stroke of uniform colour, with small variation in thickness, the process of recognising characters can be decomposed in the three steps. First the image is segmented, then each segment is transformed into a set of connected strokes (skeletonisation), which are then abstracted in a descriptor that can be used to recognise the character. The main issue with skeletonisation is the sensitivity with noise, and especially, the presence of holes in the masks. In this article, a new method for the extraction of strokes is presented, which address the problem of holes in the mask and does not use any parameters.

[481] Full text  Cyrille Berger. 2014.
Colour perception graph for characters segmentation.
In George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Chandra Kambhamettu, Maha El Choubassi, Zhigang Deng, Mark Carlson, editors, Advances in Visual Computing: 10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings, pages 598–608. In series: Lecture Notes in Computer Science #8888. Springer. ISBN: 978-3-319-14364-4, 978-3-319-14363-7.
DOI: 10.1007/978-3-319-14364-4_58.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Characters recognition in natural images is a challenging problem, asit involves segmenting characters of various colours on various background. Inthis article, we present a method for segmenting images that use a colour percep-tion graph. Our algorithm is inspired by graph cut segmentation techniques andit use an edge detection technique for filtering the graph before the graph-cut aswell as merging segments as a final step. We also present both qualitative andquantitative results, which show that our algorithm perform at slightly better andfaster to a state of the art algorithm.

[480] Full text  Mattias Tiger. 2014.
Unsupervised Spatio-Temporal Activity Learning and Recognition in a Stream Processing Framework.
Student Thesis. 103 pages. ISRN: LIU-IDA/LITH-EX-A--14/059--SE.

Learning to recognize and predict common activities, performed by objects and observed by sensors, is an important and challenging problem related both to artificial intelligence and robotics.In this thesis, the general problem of dynamic adaptive situation awareness is considered and we argue for the need for an on-line bottom-up approach.A candidate for a bottom layer is proposed, which we consider to be capable of future extensions that can bring us closer towards the goal.We present a novel approach to adaptive activity learning, where a mapping between raw data and primitive activity concepts are learned and continuously improved on-line and unsupervised. The approach takes streams of observations of objects as input and learns a probabilistic representation of both the observed spatio-temporal activities and their causal relations. The dynamics of the activities are modeled using sparse Gaussian processes and their causal relations using probabilistic graphs.The learned model supports both estimating the most likely activity and predicting the most likely future (and past) activities. Methods and ideas from a wide range of previous work are combined to provide a uniform and efficient way to handle a variety of common problems related to learning, classifying and predicting activities.The framework is evaluated both by learning activities in a simulated traffic monitoring application and by learning the flight patterns of an internally developed autonomous quadcopter system. The conclusion is that our framework is capable of learning the observed activities in real-time with good accuracy.We see this work as a step towards unsupervised learning of activities for robotic systems to adapt to new circumstances autonomously and to learn new activities on the fly that can be detected and predicted immediately.

[479] L.A. Nguyen, T.-B.-L. Nguyen and Andrzej Szalas. 2014.
On horn knowledge bases in regular description logic with inverse.
In KNOWLEDGE AND SYSTEMS ENGINEERING (KSE 2013), VOL 1, pages 37–49. In series: Advances in Intelligent Systems and Computing #Vol 244. Springer Berlin/Heidelberg. ISBN: 9783319027401.
DOI: 10.1007/978-3-319-02741-8_6.

We study a Horn fragment called Horn-RegI of the regular description logic with inverse RegI, which extends the description logic ALC with inverse roles and regular role inclusion axioms characterized by finite automata. In contrast to the well-known Horn fragmentsEL, DL-Lite, DLP, Horn-SH IQ and Horn-SROIQof description logics, Horn-RegI allows a form of the concept constructor universal restriction to appear at the left hand side of terminological inclusion axioms, while still has PTIME data complexity. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. We provide an algorithm with PTIME data complexity for checking satisfiability of Horn-RegI knowledge bases.

[478] Full text  Mattias Tiger and Fredrik Heintz. 2014.
Towards Learning and Classifying Spatio-Temporal Activities in a Stream Processing Framework.
In Ulle Endriss and Jo√£o Leite, editors, STAIRS 2014: Proceedings of the 7th European Starting AI Researcher Symposium, pages 280–289. In series: Frontiers in Artificial Intelligence and Applications #264. IOS Press. ISBN: 978-1-61499-420-6, 978-1-61499-421-3.
DOI: 10.3233/978-1-61499-421-3-280.
Fulltext: https://doi.org/10.3233/978-1-61499-421-...
Ebook: STAIRS 2014: http://ebooks.iospress.nl/volume/stairs-...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

We propose an unsupervised stream processing framework that learns a Bayesian representation of observed spatio-temporal activities and their causal relations. The dynamics of the activities are modeled using sparse Gaussian processes and their causal relations using a causal Bayesian graph. This allows the model to be efficient through compactness and sparsity in the causal graph, and to provide probabilities at any level of abstraction for activities or chains of activities. Methods and ideas from a wide range of previous work are combined and interact to provide a uniform way to tackle a variety of common problems related to learning, classifying and predicting activities. We discuss how to use this framework to perform prediction of future activities and to generate events.

[477] Oleg Burdakov, Patrick Doherty and Jonas KvarnstrŲm. 2014.
Local Search for Hop-constrained Directed Steiner Tree Problem with Application to UAV-based Multi-target Surveillance.
In Butenko, S., Pasiliao, E.L., Shylo, V., editors, Examining Robustness and Vulnerability of Networked Systems, pages 26–50. In series: NATO Science for Peace and Security Series - D: Information and Communication Security #37. IOS Press. ISBN: 978-1-61499-390-2, 978-1-61499-391-9.
DOI: 10.3233/978-1-61499-391-9-26.
Find book in another country/Hitta boken i ett annat land: http://www.worldcat.org/search?q=978-1-6...
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

We consider the directed Steiner tree problem (DSTP) with a constraint on the total number of arcs (hops) in the tree. This problem is known to be NP-hard, and therefore, only heuristics can be applied in the case of its large-scale instances.For the hop-constrained DSTP, we propose local search strategies aimed at improving any heuristically produced initial Steiner tree. They are based on solving a sequence of hop-constrained shortest path problems for which we have recently developed efficient label correcting algorithms.The presented approach is applied to finding suitable 3D locations where unmanned aerial vehicles (UAVs) can be placed to relay information gathered in multi-target monitoring and surveillance. The efficiency of our algorithms is illustrated by results of numerical experiments involving problem instances with up to 40 000 nodes and up to 20 million arcs.

[476] Full text  Oleg Burdakov, Patrick Doherty and Jonas KvarnstrŲm. 2014.
Optimal Scheduling for Replacing Perimeter Guarding Unmanned Aerial Vehicles.
Technical Report. In series: LiTH-MAT-R #2014:09. LinkŲping University Electronic Press. 16 pages.

Guarding the perimeter of an area in order to detect potential intruders is an important task in a variety of security-related applications. This task can in many circumstances be performed by a set of camera-equipped unmanned aerial vehicles (UAVs). Such UAVs will occasionally require refueling or recharging, in which case they must temporarily be replaced by other UAVs in order to maintain complete surveillance of the perimeter. In this paper we consider the problem of scheduling such replacements. We present optimal replacement strategies and justify their optimality.

[475] Full text  Oleg Burdakov, Patrick Doherty and Jonas KvarnstrŲm. 2014.
Local Search for Hop-constrained Directed Steiner Tree Problem with Application to UAV-based Multi-target Surveillance.
Technical Report. In series: LiTH-MAT-R #2014:10. LinkŲping University Electronic Press. 25 pages.

We consider the directed Steiner tree problem (DSTP) with a constraint on the total number of arcs (hops) in the tree. This problem is known to be NP-hard, and therefore, only heuristics can be applied in the case of its large-scale instances. For the hop-constrained DSTP, we propose local search strategies aimed at improving any heuristically produced initial Steiner tree. They are based on solving a sequence of hop-constrained shortest path problems for which we have recently developed ecient label correcting algorithms. The presented approach is applied to nding suitable 3D locations where unmanned aerial vehicles (UAVs) can be placed to relay information gathered in multi-target monitoring and surveillance. The eciency of our algorithms is illustrated by results of numerical experiments involving problem instances with up to 40 000 nodes and up to 20 million arcs.

[474] Full text  Gianpaolo Conte, Piotr Rudol and Patrick Doherty. 2014.
Evaluation of a Light-weight Lidar and a Photogrammetric System for Unmanned Airborne Mapping Applications: [Bewertung eines Lidar-systems mit geringem Gewicht und eines photogrammetrischen Systems fŁr Anwendungen auf einem UAV].
Photogrammetrie - Fernerkundung - Geoinformation, ??(4):287–298. E. Schweizerbart'sche Verlagsbuchhandlung.
DOI: 10.1127/1432-8364/2014/0223.
Link to article: http://www.ingentaconnect.com/content/sc...

This paper presents a comparison of two light-weight and low-cost airborne mapping systems. One is based on a lidar technology and the other on a video camera. The airborne lidar system consists of a high-precision global navigation satellite system (GNSS) receiver, a microelectromechanical system (MEMS) inertial measurement unit, a magnetic compass and a low-cost lidar scanner. The vision system is based on a consumer grade video camera. A commercial photogrammetric software package is used to process the acquired images and generate a digital surface model. The two systems are described and compared in terms of hardware requirements and data processing. The systems are also tested and compared with respect to their application on board of an unmanned aerial vehicle (UAV). An evaluation of the accuracy of the two systems is presented. Additionally, the multi echo capability of the lidar sensor is evaluated in a test site covered with dense vegetation. The lidar and the camera systems were mounted and tested on-board an industrial unmanned helicopter with maximum take-off weight of around 100 kilograms. The presented results are based on real flight-test data.

[473] Full text  Fredrik Heintz and Daniel de Leng. 2014.
Spatio-Temporal Stream Reasoning with Incomplete Spatial Information.
In Torsten Schaub, Gerhard Friedrich and Barry O'Sullivan, editors, Proceedings of the Twenty-first European Conference on Artificial Intelligence (ECAI'14), August 18-22, 2014, Prague, Czech Republic, pages 429–434. In series: Frontiers in Artificial Intelligence and Applications #263. IOS Press. ISBN: 978-1-61499-418-3, 978-1-61499-419-0.
DOI: 10.3233/978-1-61499-419-0-429.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Reasoning about time and space is essential for many applications, especially for robots and other autonomous systems that act in the real world and need to reason about it. In this paper we present a pragmatic approach to spatio-temporal stream reasoning integrated in the Robot Operating System through the DyKnow framework. The temporal reasoning is done in the Metric Temporal Logic and the spatial reasoning in the Region Connection Calculus RCC-8. Progression is used to evaluate spatio-temporal formulas over incrementally available streams of states. To handle incomplete information the underlying first-order logic is extended to a three-valued logic. When incomplete spatial information is received, the algebraic closure of the known information is computed. Since the algebraic closure might have to be re-computed every time step, we separate the spatial variables into static and dynamic variables and reuse the algebraic closure of the static variables, which reduces the time to compute the full algebraic closure. The end result is an efficient and useful approach to spatio-temporal reasoning over streaming information with incomplete information.

[472] Full text  Daniel de Leng and Fredrik Heintz. 2014.
Towards On-Demand Semantic Event Processing for Stream Reasoning.
In 17th International Conference on Information Fusion. ISBN: 9788490123553.

The ability to automatically, on-demand, apply pattern matching over streams of information to infer the occurrence of events is an important fusion functionality. Existing event detection approaches require explicit configuration of what events to detect and what streams to use as input. This paper discusses on-demand semantic event processing, and extends the semantic information integration approach used in the stream processing middleware framework DyKnow to incorporate this new feature. By supporting on-demand semantic event processing, systems can automatically configure what events to detect and what streams to use as input for the event detection. This can also include the detection of lower-level events as well as processing of streams. The semantic stream query language C-SPARQL is used to specify events, which can be seen as transformations over streams. Since semantic streams consist of RDF triples, we suggest a method to convert between RDF streams and DyKnow streams. DyKnow is integrated in the Robot Operating System (ROS) and used for example in collaborative unmanned aircraft systems missions.

[471] Full text  Mikael Nilsson, Jonas KvarnstrŲm and Patrick Doherty. 2014.
Incremental Dynamic Controllability in Cubic Worst-Case Time.
In Cesta, A; Combi, C; Laroussinie, F, editors, Proceedings of the 21st International Symposium on Temporal Representation and Reasoning (TIME), pages 17–26. In series: International Workshop on Temporal Representation and Reasoning. Proceedings #??. IEEE Computer Society Digital Library. ISBN: 978-1-4799-4227-5.
DOI: 10.1109/TIME.2014.13.

It is generally hard to predict the exact duration of an action. The uncertainty in the duration is often modeled in temporal planning by the use of upper bounds on durations, with the assumption that if an action happens to be executed more quickly, the plan will still succeed. However, this assumption is often false: If we finish cooking too early, the dinner will be cold before everyone is ready to eat. Simple Temporal Problems with Uncertainty (STPUs) allow us to model such situations. An STPU-based planner must verify that the plans it generates are executable, captured by the property of dynamic controllability. The EfficientIDC (EIDC) algorithm can do this incrementally during planning, with an amortized complexity per step of $O(n^3)$ but a worst-case complexity per step of $O(n^4)$. In this paper we show that the worst-case run-time of EIDC does occur, leading to repeated reprocessing of nodes in the STPU while verifying the dynamic controllability property. We present a new version of the algorithm, called EIDC2, which through optimal ordering of nodes avoids any need for reprocessing. This gives EIDC2 a strictly lower worst-case run-time, making it the fastest known algorithm for incrementally verifying dynamic controllability of STPUs.

[470] Full text  Per Jonsson. 2014.
Design och implementation av webbenkšter: kvalitet, svarsfrekvens och underhŚll.
Student Thesis. 10 pages. ISRN: LIU-IDA/LITH-EX-G--14/049--SE.

En webbapplikation för analys och administration av webbenkäter har designats och implementerats. Dess syfte är att maximera svarskvalitet och svarsfrekvens samt att vara underhållbar. Uppdragsgivaren Ericsson Linköping har utfärdat kravspecifikationen för applikationen. Hänsyn har tagits till aspekterna webbenkätdesign och under-hållbarhet av mjukvara. Underhållbarhetsmodeller för mjukvara med tillhörande metriker, samt designmodeller och rekommendationer för webbenkäter har studerats. Arbetets bidrag till dessa områden är en praktisk modell som tillämpar rådande forskning, i form av en webbapplikation. Applikationen har testats mot modeller och rekommendationer för underhållbarhet och enkätdesign. Applikationen uppvisar hög grad av analyserbarhet, förändringsbarhet och testbarhet, men inte stabilitet. Effekten av enkätdesignen har inte utvärderats. Modellen för underhållbarhet kan klarlägga orsak och verkan i mjukvarusystem och bidra till utveckling av programvara med hög kvalitet.

[469] Son Thanh Cao, Linh Anh Nguyen and Andrzej Szalas. 2014.
WORL: a nonmonotonic rule language for the semantic web.
, 1(1):57–69. Springer Berlin/Heidelberg.
DOI: 10.1007/s40595-013-0009-y.

We develop a new Web ontology rule language, called WORL, which combines a variant of OWL 2 RL with eDatalog ¬ . We allow additional features like negation, the minimal number restriction and unary external checkable predicates to occur at the left-hand side of concept inclusion axioms. Some restrictions are adopted to guarantee a translation into eDatalog ¬ . We also develop the well-founded semantics and the stable model semantics for WORL as well as the standard semantics for stratified WORL (SWORL) via translation into eDatalog ¬ . Both WORL with respect to the well-founded semantics and SWORL with respect to the standard semantics have PTime data complexity. In contrast to the existing combined formalisms, in WORL and SWORL negation in concept inclusion axioms is interpreted using nonmonotonic semantics.

[468] Full text  Anders WikstrŲm. 2014.
Resource allocation of drones flown in a simulated environment.
Student Thesis. 24 pages. ISRN: LIU-IDA/LITH-EX-G--14/003‚ÄĒSE.

In this report we compare three different assignment algorithms in how they can be used to assign a set of drones to get to a set of goal locations in an as resource efficient way as possible. An experiment is set up to compare how these algorithms perform in a somewhat realistic simulated environment. The Robot Operating system (ROS) is used to create the experimental environment. We found that by introducing a threshold for the Hungarian algorithm we could reduce the total time it takes to complete the problem while only sightly increasing total distance traversed by the drones.

[467] Mikael Nilsson, Jonas KvarnstrŲm and Patrick Doherty. 2014.
Efficient IDC: A Faster Incremental Dynamic Controllability Algorithm.
In Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS), pages 199–207. AAAI Press. ISBN: 978-1-57735-660-8.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essential to verify that such networks are dynamically controllable (DC) ‚Äď executable regardless of the outcomes of uncontrollable durations ‚Äď and to convert them to an executable form. We use insights from incremental DC verification algorithms to re-analyze the original verification algorithm. This algorithm, thought to be pseudo-polynomial and subsumed by an O(n5) algorithm and later an O(n4) algorithm, is in fact O(n4) given a small modification. This makes the algorithm attractive once again, given its basis in a less complex and more intuitive theory. Finally, we discuss a change reducing the amount of work performed by the algorithm.

[466] Full text  Mikael Nilsson, Jonas KvarnstrŲm and Patrick Doherty. 2014.
Classical Dynamic Controllability Revisited: A Tighter Bound on the Classical Algorithm.
In Proceedings of the 6th International Conference on Agents and Artificial Intelligence (ICAART), pages 130–141. ISBN: 978-989-758-015-4.
DOI: 10.5220/0004815801300141.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems wheresome durations are uncontrollable (determined by nature), as is often the case for actions in planning. It is essentialto verify that such networks are dynamically controllable (DC) ‚Äď executable regardless of the outcomesof uncontrollable durations ‚Äď and to convert them to an executable form. We use insights from incrementalDC verification algorithms to re-analyze the original verification algorithm. This algorithm, thought to bepseudo-polynomial and subsumed by an O(n<sup>5</sup>) algorithm and later an O(n<sup>4</sup>) algorithm, is in fact O(n<sup>4</sup>) givena small modification. This makes the algorithm attractive once again, given its basis in a less complex andmore intuitive theory. Finally, we discuss a change reducing the amount of work performed by the algorithm.

[465] Erik Sandewall. 2014.
Editorial Material: A perspective on the early history of artificial intelligence in Europe.
AI Communications, 27(1):81–86. IOS Press.
DOI: 10.3233/AIC-130585.

n/a

[464] Full text  Fredrik Heintz and Inger Erlander Klein. 2014.
The Design of Sweden's First 5-year Computer Science and Software Engineering Program.
In Proceedings of the 45th ACM Technical Symposium on Computer Science Education (SIGCSE 2014), pages 199–204. ACM Press. ISBN: 978-1-4503-2605-6.
DOI: 10.1145/2538862.2538925.

[463] Gurkan Tuna, Bilel Nefzi and Gianpaolo Conte. 2014.
Unmanned aerial vehicle-aided communications system for disaster recovery.
Journal of Network and Computer Applications, 41(??):27–36. Elsevier.
DOI: 10.1016/j.jnca.2013.10.002.

After natural disasters such as earthquakes, floods, hurricanes, tornados and fires, providing emergency management schemes which mainly rely on communications systems is essential for rescue operations. To establish an emergency communications system during unforeseen events such as natural disasters, we propose the use of a team of unmanned aerial vehicles (UAVs). The proposed system is a post-disaster solution and can be used whenever and wherever required. Each UAV in the team has an onboard computer which runs three main subsystems responsible for end-to-end communication, formation control and autonomous navigation. The onboard computer and the low-level controller of the UAV cooperate to accomplish the objective of providing local communications infrastructure. In this study, the subsystems running on each UAV are explained and evaluated by simulation studies and field tests using an autonomous helicopter. While the simulation studies address the efficiency of the end-to-end communication subsystem, the field tests evaluate the accuracy of the navigation subsystem. The results of the field tests and the simulation studies show that the proposed system can be successfully used in case of disasters to establish an emergency communications system.

2013
[462] Linh Anh Nguyen, Thi-Bich-Loc Nguyen and Andrzej Szalas. 2013.
HornDL: An Expressive Horn Description Logic with PTime Data Complexity.
In Wolfgang Faber, Domenico Lembo, editors, Web Reasoning and Rule Systems, pages 259–264. In series: Lecture Notes in Computer Science #7994. Springer Berlin/Heidelberg. ISBN: 978-3-642-39665-6, 978-3-642-39666-3.
DOI: 10.1007/978-3-642-39666-3_25.

We introduce a Horn description logic called Horn-DL, which is strictly and essentially richer than Horn- SROIQ , while still has PTime data complexity. In comparison with Horn- SROIQ , HornDL additionally allows the universal role and assertions of the form irreflexive <em>(s)</em>, ¬¨s(a,b) , a‚ČźŐłb . More importantly, in contrast to all the well-known Horn fragments EL , DL-Lite, DLP, Horn- SHIQ , Horn- SROIQ of description logics, HornDL allows a form of the concept constructor ‚Äúuniversal restriction‚ÄĚ to appear at the left hand side of terminological inclusion axioms. Namely, a universal restriction can be used in such places in conjunction with the corresponding existential restriction. In the long version of this paper, we present the first algorithm with PTime data complexity for checking satisfiability of HornDL knowledge bases.

[461] Barbara Dunin-Keplicz, Linh Anh Nguyen and Andrzej Szalas. 2013.
Horn-TeamLog: A Horn Fragment of TeamLog with PTime Data Complexity.
In Costin B«édic«é, Ngoc Thanh Nguyen, Marius Brezovan, editors, Computational Collective Intelligence. Technologies and Applications, pages 143–153. In series: Lecture Notes in Computer Science #8083. Springer Berlin/Heidelberg. ISBN: 978-3-642-40494-8, 978-3-642-40495-5.
DOI: 10.1007/978-3-642-40495-5_15.

The logic TeamLog proposed by Dunin-Kńôplicz and Verbrugge is used to express properties of agents‚Äô cooperation in terms of individual, bilateral and collective informational and motivational attitudes like beliefs, goals and intentions. In this paper we isolate a Horn fragment of TeamLog, called Horn-TeamLog, and we show that it has PTime data complexity.

[460] Linh Anh Nguyen and Andrzej Szalas. 2013.
On the Horn Fragments of Serial Regular Grammar Logics with Converse.
In Dariusz Barbucha, Manh Thanh Le, Robert J. Howlett, Lakhmi C. Jain, editors, Advanced Methods and Technologies for Agent and Multi-Agent Systems: Proceedings of the 7th KES Conference on Agent and Multi-Agent Systems - Technologies and Applications (KES-AMSTA 2013), pages 225–234. In series: Frontiers in Artificial Intelligence and Applications #252. IOS Press. ISBN: 978-1-61499-253-0.
DOI: 10.3233/978-1-61499-254-7-225.

We study Horn fragments of serial multimodal logics which are characterized by regular grammars with converse. Such logics are useful for reasoning about epistemic states of multiagent systems as well as similarity-based approximate reasoning. We provide the first algorithm with PTIME data complexity for checking satisfiability of a Horn knowledge base in a serial regular grammar logic with converse.

[459] Jan Maluszynski and Andrzej Szalas. 2013.
Partiality and Inconsistency in Agents' Belief Bases.
In Dariusz Barbucha, Manh Thanh Le, Robert J. Howlett, Lakhmi C. Jain, editors, Advanced Methods and Technologies for Agent and Multi-Agent Systems: Proceedings of the 7th KES Conference on Agent and Multi-Agent Systems - Technologies and Applications (KES-AMSTA 2013), pages 3–17. In series: Frontiers in Artificial Intelligence and Applications #252. IOS Press. ISBN: 978-1-61499-253-0.
DOI: 10.3233/978-1-61499-254-7-3.

Agents' beliefs can be incomplete and partially inconsistent. The process of agents' belief formation in such contexts has to be supported by suitable tools allowing one to express a variety of inconsistency resolving and nonmonotonic reasoning techniques.In this paper we discuss 4QL*, a general purpose rule-based query language allowing one to use rules with negation in the premises and in the conclusions of rules. It is based on a simple and intuitive semantics and provides uniform tools for lightweight versions of well-known forms of nonmonotonic reasoning. In addition, it is tractable w.r.t. data complexity and captures PTIME queries, so can be used in real-world applications.Reasoning in 4QL* is based on well-supported models. We simplify and at the same time generalize previous definitions of well-supported models and develop a new algorithm for computing such models.

[458] Barbara Dunin-Keplicz, Alina Strachocka, Andrzej Szalas and Rineke Verbrugge. 2013.
Perceiving Speech Acts under Incomplete and Inconsistent Information.
In Dariusz Barbucha, Manh Thanh Le, Robert J. Howlett, Lakhmi C. Jain, editors, Advanced Methods and Technologies for Agent and Multi-Agent Systems: Proceedings of the 7th KES Conference on Agent and Multi-Agent Systems - Technologies and Applications (KES-AMSTA 2013), pages 255–264. In series: Frontiers in Artificial Intelligence and Applications #252. IOS Press. ISBN: 978-1-61499-253-0.
DOI: 10.3233/978-1-61499-254-7-255.

This paper discusses an implementation of four speech acts: assert, concede, request and challenge in a paraconsistent framework. A natural four-valued model of interaction yields multiple new cognitive situations. They are analyzed in the context of communicative relations, which partially replace the concept of trust. These assumptions naturally lead to six types of situations, which often require performing conflict resolution and belief revision.The particular choice of a rule-based, DATALOG$^{\neg \neg}$-like query language 4QL as a four-valued implementation framework ensures that, in contrast to the standard two-valued approaches, tractability of the model is achieved.

[457] Barbara Dunin-Keplicz and Andrzej Szalas. 2013.
Taming Complex Beliefs.
In Ngoc Thanh Nguyen, editor, Transactions on Computational Collective Intelligence XI, pages 1–21. In series: Lecture Notes in Computer Science #8065. Springer. ISBN: 978-3-642-41775-7, 978-3-642-41776-4.
DOI: 10.1007/978-3-642-41776-4_1.

A novel formalization of beliefs in multiagent systems has recently been proposed by Dunin-Kńôplicz and SzaŇāas. The aim has been to bridge the gap between idealized logical approaches to modeling beliefs and their actual implementations. Therefore the stages of belief acquisition, intermediate reasoning and final belief formation have been isolated and analyzed. In conclusion, a novel semantics reflecting those stages has been provided. This semantics is based on the new concept of epistemic profile, reflecting agent‚Äôs reasoning capabilities in a dynamic and unpredictable environment. The presented approach appears suitable for building complex belief structures in the context of incomplete and/or inconsistent information. One of original ideas is that of epistemic profiles serving as a tool for transforming preliminary beliefs into final ones. As epistemic profile can be devised both on an individual and a group level in analogical manner, a uniform treatment of single agent and group beliefs has been achieved.In the current paper these concepts are further elaborated. Importantly, we indicate an implementation framework ensuring tractability of reasoning about beliefs, propose the underlying methodology and illustrate it on an example.

[456] Full text  Patrick Doherty, Fredrik Heintz and Jonas KvarnstrŲm. 2013.
Robotics, Temporal Logic and Stream Reasoning.
In Proceedings of Logic for Programming Artificial Intelligence and Reasoning (LPAR), 2013.

[455] Fredrik Heintz and Inger Erlander Klein. 2013.
CivilingenjŲr i Mjukvaruteknik vid LinkŲpings universitet: mŚl, design och erfarenheter.
In S. Vikstr√∂m, R. Andersson, F. Georgsson, S. Gunnarsson, J. Malmqvist, S. P√•lsson och D. Raudberget, editors, Proceedings of 4:de Utvecklingskonferensen fŲr Sveriges ingenjŲrsutbildningar (UtvSvIng). In series: UMINF #13:21.

H√∂sten 2013 startade Link√∂pings universitet den f√∂rsta civilingenj√∂rsutbildningen i Mjukvaruteknik. Utbildningens m√•l √§r att bland annat att ge ett helhetsperspektiv p√• modern storskalig mjukvaruutveckling, ge en gedigen grund i datavetenskap och computational thinking samt fr√§mja entrepren√∂rskap och innovation. Studenternas gensvar har varit √∂ver f√∂rv√§ntan med √∂ver 600 s√∂kande till de 30 platserna varav 134 f√∂rstahandss√∂kande. H√§r presenterar vi programmets vision, m√•l, designprinciper samt det f√§rdiga programmet. En viktig f√∂rebild √§r ACM/IEEE Computer Science Curricula som precis kommit i en ny uppdaterad version. Tre pedagogiska id√©er vi har f√∂ljt √§r (1) att anv√§nda projektkurser f√∂r att integrera teori och praktik samt ge erfarenhet i den vanligaste arbetsformen i n√§ringslivet; (2) att undervisa i flera olika programspr√•k och flera olika programutvecklingsmetodiker f√∂r att ge en plattform att ta till sig det senaste p√• omr√•det; och (3) att inf√∂ra en programsammanh√•llande kurs i ingenj√∂rsprofessionalism i √•rskurs 1‚Äď3 som ger studenterna verktyg att reflektera √∂ver sitt eget l√§rande, att jobba i n√§ringslivet samt sin professionella yrkesroll. Artikeln avslutas med en diskussion om viktiga aspekter som computational thinking och ACM/IEEE CS Curricula.

[454] Fredrik Heintz and Tommy Fšrnqvist. 2013.
Ňterkoppling genom automatršttning.
In Proceedings of 4:de Utvecklingskonferensen fŲr Sveriges ingenjŲrsutbildningar (UtvSvIng).
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Vi har undersökt olika former av återkoppling genom automaträttning i en kurs i datastrukturer och algoritmer. 2011 undersökte vi effekterna av tävlingsliknande moment som också använder automaträttning. 2012 införde vi automaträttning av laborationerna. Vi undersökte då hur återkoppling genom automaträttning påverkar studenternasarbetssätt, prestationsgrad och relation till den examinerande personalen. Genom automaträttning får studenterna omedelbar återkoppling om deras program är tillräckligt snabbt och ger rätt svar på testdata. När programmet är korrekt och resurseffektivt kontrollerar kursassistenterna att programmet även uppfyller andra krav som att vara välskrivet och välstrukturerat. Efter kursen undersökte vi studenternas inställning till och upplevelse av automaträttning genom en enkät. Resultaten är att studenterna är positiva till automaträttning (80% av alla som svarade) och att den påverkade studenternas sätt att arbeta huvudsakligen positivt. Till exempel svarade 50% att de ansträngde sig hårdare tack vare automaträttningen. Dessutom blir rättningen mer objektiv då den görs på exakt samma sätt för alla. Vår slutsats är att återkoppling genom automaträttning ger positiva effekter och upplevs som positiv av studenterna.

[453] Patrick Doherty and Andrzej Szalas. 2013.
Automated Generation of Logical Constraints on Approximation Spaces Using Quantifier Elimination.
Fundamenta Informaticae, 127(1-4):135–149. IOS Press.
DOI: 10.3233/FI-2013-900.
Note: Funding Agencies|Swedish Research Council (VR) Linnaeus Center CADICS||ELLIIT Excellence Center at Linkoping-Lund in Information Technology||CUAS project||SSF, the Swedish Foundation for Strategic Research||

This paper focuses on approximate reasoning based on the use of approximation spaces. Approximation spaces and the approximated relations induced by them are a generalization of the rough set-based approximations of Pawlak. Approximation spaces are used to define neighborhoods around individuals and rough inclusion functions. These in turn are used to define approximate sets and relations. In any of the approaches, one would like to embed such relations in an appropriate logical theory which can be used as a reasoning engine for specific applications with specific constraints. We propose a framework which permits a formal study of the relationship between properties of approximations and properties of approximation spaces. Using ideas from correspondence theory, we develop an analogous framework for approximation spaces. We also show that this framework can be strongly supported by automated techniques for quantifier elimination.

[452] Full text  Robin Murphy and Alexander Kleiner. 2013.
A Community-Driven Roadmap for the Adoption of Safety Security and Rescue Robots.
In Safety, Security, and Rescue Robotics (SSRR), 2013 IEEE International Symposium on, pages 1–5. IEEE conference proceedings. ISBN: 978-1-4799-0879-0.
DOI: 10.1109/SSRR.2013.6719375.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

The IEEE Safety, Security, and Rescue Robotics community has created a roadmap for producing unmanned systems that could be adopted by the Public Safety sector within 10 years, given appropriate R&amp;D investment especially in human-robot interaction and perception. The five applications expected to be of highest value to the Public Safety community, highest value first, are: assisting with routine inspection of the critical infrastructure, ‚Äúchronic emergencies‚ÄĚ such as firefighting, hazardous material spills, port inspection, and damage estimation after a disaster. The technical feasibility of the applications were ranked, with the most attractive scenario, infrastructure inspection, rated as the second easiest scenario; this suggests the maturity of robotics technology is beginning to match stakeholder needs. Each of the five applications were discussed in terms of the six broad enabling technology areas specified in the current National Robotics Initiative Roadmap (perception, human-robot interaction, mechanisms, modeling and simulation, control and planning, and testing and evaluation) and nine specific capabilities identified by the community as being essential to commercialization (communication, alerting, localization, fault tolerance, mapping, manpower needs, plug and play capabilities, multiple users, and multiple robots). The community believes that perception and human-robot interaction are the two biggest barriers to adoption, and require more research, given that their low technical maturity (3rd and 6th rank respectively). However, each of the specific capabilities needed for commercialization are being addressed by current research and could be achieved within 10 years with sustained funding.

[451] Jakob Pogulis. 2013.
Testramverk fŲr distribuerade system.
Student Thesis. 46 pages. ISRN: LIU-IDA/LITH-EX-G--13/010--SE.

When developing software that is meant to be distributed over several different computers and several different networks while still working together against a common goal there is a challenge in testing how updates within a single component will affect the system as a whole. Even if the performance of that specific component increases that is no guarantee for the increased performance of the entire system. Traditional methods of testing software becomes both hard and tedious when several different machines has to be involved for a single test and all of those machines has to be synchronized as well.This thesis has resulted in an exemplary application suite for testing distributed software. The thesis describes the method used for implementation as well as a description of the actual application suite that was developed. During the development several important factors and improvements for such a system was identified, which are described at the end of the thesis even though some of them never made it into the actual implementation. The implemented application suite could be used as a base when developing a more complete system in order to distribute tests and applications that has to run in a synchronized manner with the ability to report the results of each individual component.

[450] Full text  Christian Dornhege, Alexander Kleiner and Andreas Kolling. 2013.
Coverage Search in 3D.
In Safety, Security, and Rescue Robotics (SSRR), 2013 IEEE International Symposium on, pages 1–8. IEEE. ISBN: 978-1-4799-0879-0.
DOI: 10.1109/SSRR.2013.6719340.
Note: Accepted for Publication.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Searching with a sensor for objects and to observe parts of a known environment efficiently is a fundamental prob- lem in many real-world robotic applications such as household robots searching for objects, inspection robots searching for leaking pipelines, and rescue robots searching for survivors after a disaster. We consider the problem of identifying and planning efficient view point sequences for covering complex 3d environments. We compare empirically several variants of our algorithm that allow to trade-off schedule computation against execution time. Our results demonstrate that, despite the intractability of the overall problem, computing effective solutions for coverage search in real 3d environments is feasible.

[449] Andrzej Szalas. 2013.
How an agent might think.
Logic journal of the IGPL (Print), 21(3):515–535. Oxford University Press (OUP): Policy A - Oxford Open Option A.
DOI: 10.1093/jigpal/jzs051.

The current article is devoted to extensions of the rule query language 4QL proposed by MaŇāuszyŇĄski and SzaŇāas. 4QL is a Datalog<sup>¬¨¬¨</sup>-like language, allowing one to use rules with negation in heads and bodies of rules. It is based on a simple and intuitive semantics and provides uniform tools for lightweight versions of well-known forms of non-monotonic reasoning. In addition, 4QL is tractable w.r.t. data complexity and captures PTime queries. In the current article we relax most of restrictions of 4QL, obtaining a powerful but still tractable query language 4QL<sup>+</sup>. In its development we mainly focused on its pragmatic aspects: simplicity, tractability and generality. In the article we discuss our approach and choices made, define a new, more general semantics and investigate properties of 4QL<sup>+</sup>.

[448] Full text  Fredrik Heintz. 2013.
Semantically Grounded Stream Reasoning Integrated with ROS.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5935–5942. In series: IEEE International Conference on Intelligent Robots and Systems. Proceedings #??. IEEE conference proceedings. ISBN: 978-146736358-7.
DOI: 10.1109/IROS.2013.6697217.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

High level reasoning is becoming essential to autonomous systems such as robots. Both the information available to and the reasoning required for such autonomous systems is fundamentally incremental in nature. A stream is a flow of incrementally available information and reasoning over streams is called stream reasoning. Incremental reasoning over streaming information is necessary to support a number of important robotics functionalities such as situation awareness, execution monitoring, and decision making.This paper presents a practical framework for semantically grounded temporal stream reasoning called DyKnow. Incremental reasoning over streams is achieved through efficient progression of temporal logical formulas. The reasoning is semantically grounded through a common ontology and a specification of the semantic content of streams relative to the ontology. This allows the finding of relevant streams through semantic matching. By using semantic mappings between ontologies it is also possible to do semantic matching over multiple ontologies. The complete stream reasoning framework is integrated in the Robot Operating System (ROS) thereby extending it with a stream reasoning capability.

[447] Full text  Gianpaolo Conte, Alexander Kleiner, Piotr Rudol, Karol Korwel, Mariusz Wzorek and Patrick Doherty. 2013.
Performance evaluation of a light weight multi-echo LIDAR for unmanned rotorcraft applications.
In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W2. In series: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences #??. Copernicus Gesellschaft MBH.

The paper presents a light-weight and low-cost airborne terrain mapping system. The developed Airborne LiDAR Scanner (ALS) sys- tem consists of a high-precision GNSS receiver, an inertial measurement unit and a magnetic compass which are used to complement a LiDAR sensor in order to compute the terrain model. Evaluation of the accuracy of the generated 3D model is presented. Additionally, a comparison is provided between the terrain model generated from the developed ALS system and a model generated using a commer- cial photogrammetric software. Finally, the multi-echo capability of the used LiDAR sensor is evaluated in areas covered with dense vegetation. The ALS system and camera systems were mounted on-board an industrial unmanned helicopter of around 100 kilograms maximum take-off weight. Presented results are based on real flight-test data.

[446] Full text  Andreas Kolling, Alexander Kleiner and Piotr Rudol. 2013.
Fast Guaranteed Search With Unmanned Aerial Vehicles.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), pages 6013–6018. In series: IEEE International Conference on Intelligent Robots and Systems. Proceedings #??. IEEE.
DOI: 10.1109/IROS.2013.6697229.

In this paper we consider the problem of searching for an arbitrarily smart and fast evader in a large environment with a team of unmanned aerial vehicles (UAVs) while providing guarantees of detection. Our emphasis is on the fast execution of efficient search strategies that minimize the number of UAVs and the search time. We present the first approach for computing fast search strategies utilizing additional searchers to speed up the execution time and thereby enabling large scale UAV search. In order to scale to very large environments when using UAVs one would either have to overcome the energy limitations of UAVs or pay the cost of utilizing additional UAVs to speed up the search. Our approach is based on coordinating UAVs on sweep lines, covered by the UAV sensors, that move simultaneously through an environment. We present some simulation results that show a significant reduction in execution time when using multiple UAVs and a demonstration of a real system with three ARDrones.

[445] Full text  Karen Petersen, Alexander Kleiner and Oskar von Stryk. 2013.
Fast Task-Sequence Allocation for Heterogeneous Robot Teams with a Human in the Loop.
In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), pages 1648–1655. In series: IEEE International Conference on Intelligent Robots and Systems. Proceedings #??. IEEE.
DOI: 10.1109/IROS.2013.6696570.

Efficient task allocation with timing constraints to a team of possibly heterogeneous robots is a challenging problem with application, e.g., in search and rescue. In this paper a mixed-integer linear programming (MILP) approach is proposed for assigning heterogeneous robot teams to the simultaneous completion of sequences of tasks with specific requirements such as completion deadlines. For this purpose our approach efficiently combines the strength of state of the art Mixed Integer Linear Programming (MILP) solvers with human expertise in mission scheduling. We experimentally show that simple and intuitive inputs by a human user have substantial impact on both computation time and quality of the solution. The presented approach can in principle be applied to quite general missions for robot teams with human supervision.

[444] Full text  Christopher Bergdahl. 2013.
Modeling Air Combat with Influence Diagrams.
Student Thesis. 64 pages. ISRN: LIU-IDA/LITH-EX-A--13/031--SE.

Air combat is a complex situation, training for it and analysis of possible tactics are time consuming and expensive. In order to circumvent those problems, mathematical models of air combat can be used. This thesis presents air combat as a one-on-one influence diagram game where the influence diagram allows the dynamics of the aircraft, the preferences of the pilots and the uncertainty of decision making in a structural and transparent way to be taken into account. To obtain the players’ game optimal control sequence with respect to their preferences, the influence diagram has to be solved. This is done by truncating the diagram with a moving horizon technique and determining and implementing the optimal controls for a dynamic game which only lasts a few time steps.The result is a working air combat model, where a player estimates the probability that it resides in any of four possible states. The pilot’s preferences are modeled by utility functions, one for each possible state. In each time step, the players are maximizing the cumulative sum of the utilities for each state which each possible action gives. These are weighted with the corresponding probabilities. The model is demonstrated and evaluated in a few interesting aspects. The presented model offers a way of analyzing air combat tactics and maneuvering as well as a way of making autonomous decisions in for example air combat simulators.

[443] Full text  Johan Fredborg. 2013.
Spam filter for SMS-traffic.
Student Thesis. 82 pages. ISRN: LIU-IDA/LITH-EX-A--13/021-SE.

Communication through text messaging, SMS (Short Message Service), is nowadays a huge industry with billions of active users. Because of the huge userbase it has attracted many companies trying to market themselves through unsolicited messages in this medium in the same way as was previously done through email. This is such a common phenomenon that SMS spam has now become a plague in many countries.This report evaluates several established machine learning algorithms to see how well they can be applied to the problem of filtering unsolicited SMS messages. Each filter is mainly evaluated by analyzing the accuracy of the filters on stored message data. The report also discusses and compares requirements for hardware versus performance measured by how many messages that can be evaluated in a fixed amount of time.The results from the evaluation shows that a decision tree filter is the best choice of the filters evaluated. It has the highest accuracy as well as a high enough process rate of messages to be applicable. The decision tree filter which was found to be the most suitable for the task in this environment has been implemented. The accuracy in this new implementation is shown to be as high as the implementation used for the evaluation of this filter.Though the decision tree filter is shown to be the best choice of the filters evaluated it turned out the accuracy is not high enough to meet the specified requirements. It however shows promising results for further testing in this area by using improved methods on the best performing algorithms.

[442] Full text  Fredrik Heintz and Daniel de Leng. 2013.
Semantic Information Integration with Transformations for Stream Reasoning.
In 16th International Conference on Information Fusion, pages 445–452. IEEE. ISBN: 978-605-86311-1-3.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

The automatic, on-demand, integration of information from multiple diverse sources outside the control of the application itself is central to many fusion applications. An important problem is to handle situations when the requested information is not directly available but has to be generated or adapted through transformations. This paper extends the semantic information integration approach used in the stream-based knowledge processing middleware DyKnow with support for finding and automatically applying transformations. Two types of transformations are considered. Automatic transformation between different units of measurements and between streams of different types. DyKnow achieves semantic integration by creating a common ontology, specifying the semantic content of streams relative to the ontology and using semantic matching to find relevant streams. By using semantic mappings between ontologies it is also possible to do semantic matching over multiple ontologies. The complete stream reasoning approach is integrated in the Robot Operating System (ROS) and used in collaborative unmanned aircraft systems missions.

[441] Full text  Mikael Nilsson. 2013.
On the Complexity of Finding Spanner Paths.
In Sandor P. Fekete, editor, Booklet of Abstracts, The European Workshop on Computational Geometry (EuroCG), pages 77–80.
Booklet of Abstracts: http://www.ibr.cs.tu-bs.de/alg/eurocg13/...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

We study the complexity of finding so called spanner paths between arbitrary nodes in Euclidean graphs. We study both general Euclidean graphs and a special type of graphs called Integer Graphs. The problem is proven NP-complete for general Euclidean graphs with non-constant stretches (e.g. (2n)^(3/2) where n denotes the number of nodes in the graph). An algorithm solving the problem in O(2^(0.822n)) is presented. Integer graphs are simpler and for these special cases a better algorithm is presented. By using a partial order of so called Images the algorithm solves the spanner path problem using O(2^(c(\log n)^2)) time, where c is a constant depending only on the stretch.

[440] Full text  Cyrille Berger. 2013.
Toward rich geometric map for SLAM: online detection of planets in 2D LIDAR.
Journal of Automation, Mobile Robotics & Intelligent Systems, 7(1):35–41.
Link to article: http://www.jamris.org/archive.php

Rich geometric models of the environment are needed for robots to carry out their missions. However a robot operating in a large environment would require a compact representation. In this article, we present a method that relies on the idea that a plane appears as a line segment in a 2D scan, and that by tracking those lines frame after frame, it is possible to estimate the parameters of that plane. The method is divided in three steps: fitting line segments on the points of the 2D scan, tracking those line segments in consecutive scan and estimating the parameters with a graph based SLAM (Simultaneous Localisation And Mapping) algorithm.

[439] Full text  Patrick Doherty, Fredrik Heintz and Jonas KvarnstrŲm. 2013.
High-level Mission Specification and Planning for Collaborative Unmanned Aircraft Systems using Delegation.
Unmanned Systems, 1(1):75–119. World Scientific.
DOI: 10.1142/S2301385013500052.

Automated specification, generation and execution of high level missions involving one or more heterogeneous unmanned aircraft systems is in its infancy. Much previous effort has been focused on the development of air vehicle platforms themselves together with the avionics and sensor subsystems that implement basic navigational skills. In order to increase the degree of autonomy in such systems so they can successfully participate in more complex mission scenarios such as those considered in emergency rescue that also include ongoing interactions with human operators, new architectural components and functionalities will be required to aid not only human operators in mission planning, but also the unmanned aircraft systems themselves in the automatic generation, execution and partial verification of mission plans to achieve mission goals. This article proposes a formal framework and architecture based on the unifying concept of delegation that can be used for the automated specification, generation and execution of high-level collaborative missions involving one or more air vehicles platforms and human operators. We describe an agent-based software architecture, a temporal logic based mission specification language, a distributed temporal planner and a task specification language that when integrated provide a basis for the generation, instantiation and execution of complex collaborative missions on heterogeneous air vehicle systems. A prototype of the framework is operational in a number of autonomous unmanned aircraft systems developed in our research lab.

[438] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2013.
Stream-Based Hierarchical Anchoring.
KŁnstliche Intelligenz, 27(2):119–128. Springer.
DOI: 10.1007/s13218-013-0239-2.

Autonomous systems situated in the real world often need to recognize, track, and reason about various types of physical objects. In order to allow reasoning at a symbolic level, one must create and continuously maintain a correlation between symbols denoting physical objects and sensor data being collected about them, a process called anchoring.In this paper we present a stream-based hierarchical anchoring framework. A classification hierarchy is associated with expressive conditions for hypothesizing the type and identity of an object given streams of temporally tagged sensor data. The anchoring process constructs and maintains a set of object linkage structures representing the best possible hypotheses at any time. Each hypothesis can be incrementally generalized or narrowed down as new sensor data arrives. Symbols can be associated with an object at any level of classification, permitting symbolic reasoning on different levels of abstraction. The approach is integrated in the DyKnow knowledge processing middleware and has been applied to an unmanned aerial vehicle traffic monitoring application.

[437] Full text  HŚkan Warnquist, Jonas KvarnstrŲm and Patrick Doherty. 2013.
Exploiting Fully Observable and Deterministic Structures in Goal POMDPs.
In Daniel Borrajo, Subbarao Kambhampati, Angelo Oddi, Simone Fratini, editors, Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS), pages 242–250. AAAI Press. ISBN: 978-1-57735-609-7.
Link to full text: http://www.aaai.org/ocs/index.php/ICAPS/...

When parts of the states in a goal POMDP are fully observable and some actions are deterministic it is possibleto take advantage of these properties to efficiently generate approximate solutions. Actions that deterministically affect the fully observable component of the world state can be abstracted away and combined into macro actions, permitting a planner to converge more quickly. This processing can be separated from the main search procedure, allowing us to leverage existing POMDP solvers. Theoretical results show how a POMDP can be analyzed to identify the exploitable properties and formal guarantees are provided showing that the use of macro actions preserves solvability. The efficiency of the method is demonstrated with examples when used in combination with existing POMDP solvers.

[436] Full text  Mikael Nilsson, Jonas KvarnstrŲm and Patrick Doherty. 2013.
Incremental Dynamic Controllability Revisited.
In Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS). AAAI Press. ISBN: 978-1-57735-609-7.

Simple Temporal Networks with Uncertainty (STNUs) allow the representation of temporal problems where some durations are determined by nature, as is often the case for actions in planning. As such networks are generated it is essential to verify that they are dynamically controllable ‚Äď executable regardless of the outcomes of uncontrollable durations ‚Äď and to convert them to a dispatchable form. The previously published FastIDC algorithm achieves this incrementally and can therefore be used efficiently during plan construction. In this paper we show that FastIDC is not sound when new constraints are added, sometimes labeling networks as dynamically controllable when they are not. We analyze the algorithm, pinpoint the cause, and show how the algorithm can be modified to correctly detect uncontrollable networks.

[435] Full text  Andreas Kolling and Alexander Kleiner. 2013.
Multi-UAV Trajectory Planning for Guaranteed Search.
In Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013), pages 79–86. The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). ISBN: 978-1-4503-1993-5.
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

We consider the problem of detecting all moving and evading targets in 2.5D environments with teams of UAVs. Targets are assumed to be fast and omniscient while UAVs are only equipped with limited range detection sensors and have no prior knowledge about the location of targets. We present an algorithm that, given an elevation map of the environment, computes synchronized trajectories for the UAVs to guarantee the detection of all targets. The approach is based on coordinating the motion of multiple UAVs on sweep lines to clear the environment from contamination, which represents the possibility of an undetected target being located in an area. The goal is to compute trajectories that minimize the number of UAVs needed to execute the guaranteed search. This is achieved by converting 2D strategies, computed for a polygonal representation of the environment, to 2.5D strategies. We present methods for this conversion and consider cost of motion and visibility constraints. Experimental results demonstrate feasibility and scalability of the approach. Experiments are carried out on real and artificial elevation maps and provide the basis for future deployments of large teams of real UAVs for guaranteed search.

[434] Full text  Alexander Kleiner, A. Farinelli, S. Ramchurn, B. Shi, F. Maffioletti and R. Reffato. 2013.
RMASBench: Benchmarking Dynamic Multi-Agent Coordination in Urban Search and Rescue.
In Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013), pages 1195–1196. The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). ISBN: 978-1-4503-1993-5.
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

We propose RMASBench, a new benchmarking tool based on the RoboCup Rescue Agent simulation system, to easily compare coordination approaches in a dynamic rescue scenario. In particular, we offer simple interfaces to plug-in coordination algorithms without the need for implementing and tuning low-level agents behaviors. Moreover, we add to the realism of the simulation by providing a large scale crowd simulator, which exploits GPUs parallel architecture, to simulate the behavior of thousands of agents in real time. Finally, we focus on a specific coordination problem where fire fighters must combat fires and prevent them from spreading across the city. We formalize this problem as a Distributed Constraint Optimization Problem and we compare two state-of-the art solution techniques: DSA and MaxSum. We perform an extensive empirical evaluation of such techniques considering several standard measures for performance (e.g. damages to buildings) and coordination overhead (e.g., message exchanged and non concurrent constraint checks). Our results provide interesting insights on limitations and benefits of DSA and MaxSum in our rescue scenario and demonstrate that RMASBench offers powerful tools to compare coordination algorithms in a dynamic environment.

[433] H. Levent Akin, Nobuhiro Ito, Adam Jacoff, Alexander Kleiner, Johannes Pellenz and Arnoud Visser. 2013.
RoboCup Rescue Robot and Simulation Leagues.
The AI Magazine, 34(1):????. AAAI Press.
Link to journal: http://www.aaai.org/ojs/index.php/aimaga...
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

The RoboCup Rescue Robot and Simulation competitions have been held since 2000. The experience gained during these competitions has increased the maturity level of the field, which allowed deploying robots after real disasters (e.g. Fukushima Daiichi nuclear disaster). This article provides an overview of these competitions and highlights the state of the art and the lessons learned.

[432] Full text  Alexander Kleiner and Andreas Kolling. 2013.
Guaranteed Search With Large Teams of Unmanned Aerial Vehicles.
In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages 2977–2983. In series: Robotics and Automation (ICRA), 2013 IEEE International Conference on #??. IEEE conference proceedings. ISBN: 978-1-4673-5641-1.
DOI: 10.1109/ICRA.2013.6630990.

We consider the problem of detecting moving and evading targets by a team of coordinated unmanned aerial vehicles (UAVs) in large and complex 2D and 2.5D environments. Our approach is based on the coordination of 2D sweep lines that move through the environment to clear it from all contamination, representing the possibility of a target being located in an area, and thereby detecting all targets. The trajectories of the UAVs are implicitly given by the motion of these sweep lines and their costs are determined by the number of UAVs needed. A novel algorithm that computes low cost coordination strategies of the UAV sweep lines in simply connected polygonal environments is presented. The resulting strategies are then converted to strategies clearing multiply connected and 2.5D environments. Experiments on real and artificial elevation maps with complex visibility constraints are presented and demonstrate the feasibility and scalability of the approach. The algorithms used for the experiments are made available on a public repository.

[431] Full text  Quirin Hamp, Omar Gorgis, Patrick Labenda, Marc Neumann, Thomas Predki, Leif Heckes, Alexander Kleiner and Leonard Reindl. 2013.
Study of efficiency of USAR operations with assistive technologies.
Advanced Robotics, 27(5):337–350.
DOI: 10.1080/01691864.2013.763723.
Note: Funding Agencies|German Federal Ministry of Education and Research|13N9759|German Federal Agency for Technical Relief (THW)||RIF e.V.||JT-electronic GmbH||carat robotic innovation GmbH||Berlin- Oberspree Sondermaschinenbau GmbH (BOS)||SEEBA||
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

This paper presents presents a study on eciency of Urban Search and Rescue (USAR) missions that has been carried out within the framework of the German research project I-LOV. After three years of development, first field tests have been carried out in 2011 by professionals such as the Rapid Deployment Unit for Salvage Operations Abroad (SEEBA). We present results from evaluating search teams in simulated USAR scenarios equipped with newly developed technical search means and digital data input terminals developed in the I-LOV project. In particular, USAR missions assisted by the ‚Äúbioradar‚ÄĚ, a ground-penetrating radar system for the detection of humanoid movements, a semi-active video probe of more than 10 m length for rubble pile exploration, a snake-like rescue robot, and the decision support system FRIEDAA were evaluated and compared with conventional USAR missions. Results of this evaluation indicate that the developed technologies represent an advantages for USAR missions, which are discussed in this paper.

[430] Full text  Linh Anh Nguyen and Andrzej Szalas. 2013.
Logic-Based Roughification.
In Andrzej Skowron, Zbigniew Suraj, editors, Rough Sets and Intelligent Systems - Professor Zdzis?aw Pawlak in Memoriam (vol. I), pages 517–543. In series: Intelligent Systems Reference Library #42. Springer Berlin/Heidelberg. ISBN: 978-3-642-30343-2.
DOI: 10.1007/978-3-642-30344-9_19.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/13601690
find book in another country/hitta boken i ett annat land: http://www.worldcat.org/title/rough-sets...

This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being.This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches.We are proud to offer the readers this book.

[429] Barbara Dunin-Keplicz and Andrzej Szalas. 2013.
Distributed Paraconsistent Belief Fusion.
In Giancarlo Fortino , Costin Badica , Michele Malgeri and Rainer Unland, editors, Intelligent Distributed Computing VI: Proceedings of the 6th International Symposium on Intelligent Distributed Computing - IDC 2012, Calabria, Italy, September 2012, pages 59–69. In series: Studies in Computational Intelligence #446. Springer Berlin/Heidelberg. ISBN: 978-3-642-32523-6, 978-3-642-32524-3.
DOI: 10.1007/978-3-642-32524-3_9.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/13601893

The current paper is devoted to belief fusion when information sources may deliver incomplete and inconsistent information. In such cases paraconsistent and commonsense reasoning techniques can be used to complete missing knowledge and disambiguate inconsistencies. We propose a novel, realistic model of distributed belief fusion and an implementation framework guaranteeing its tractability.

[428] Full text  C. Dornhege and Alexander Kleiner. 2013.
A Frontier-Void-Based Approach for Autonomous Exploration in 3D.
Advanced Robotics, 27(6):459–468. Taylor and Francis.
DOI: 10.1080/01691864.2013.763720.
Note: Funding Agencies|Deutsche Forschungsgemeinschaft in the Transregional Collaborative Research Center|SFB/TR8|
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

We consider the problem of an autonomous robot searching for objects in unknown 3d space. Similar to the well known frontier-based exploration in 2d, the problem is to determine a minimal sequence of sensor viewpoints until the entire search space has been explored. We introduce a novel approach that combines the two concepts of voids, which are unexplored volumes in 3d, and frontiers, which are regions on the boundary between voids and explored space. Our approach has been evaluated on a mobile platform equipped with a manipulator searching for victims in a simulated USAR setup. First results indicate the real-world capability and search efficiency of the proposed method.

2012
[427] Patrick Doherty and John-Jules Ch. Meyer. 2012.
On the Logic of Delegation - Relating Theory and Practice.
In Fabio Paglieri, Luca Tummolini, Rino Falcone, Maria Miceli, editors, The Goals of Cognition: Essays in honour of Cristiano Castelfranchi, pages 467–496. College Publications. ISBN: 978-1848900943.
Find book in another country/Hitta boken i ett annat land: http://www.worldcat.org/search?q=978-184...

Research with collaborative robotic systems has much to gain by leveraging concepts and ideas from the areas of multi-agent systems and the social sciences. In this paper we propose an approach to formalizing and grounding important aspects of collaboration in a collaborative system shell for robotic systems. This is done primarily in terms of the concept of delegation, where delegation will be instantiated as a speech act. The formal characterization of the delegation speech act is based on a preformal theory of delegation proposed by Falcone and Castelfranchi. We show how the delegation speech act can in fact be used to formally ground an abstract characterization of delegation into a FIPA-compliant implementation in an agent-oriented language such as JADE, as part of a collaborative system shell for robotic systems. The collaborative system shell has been developed as a prototype and used in collaborative missions with multiple unmanned aerial vehicle systems.

[426] Patrick Doherty, Fredrik Heintz and David Landťn. 2012.
A Distributed Task Specification Language for Mixed-Initiative Delegation.
In Nirmit Desai, Alan Liu, Michael Winikoff, editors, Principles and Practice of Multi-Agent Systems: 13th International Conference, PRIMA 2010, Kolkata, India, November 12-15, 2010, Revised Selected Papers, pages 42–57. In series: Lecture Notes in Computer Science #7057. Springer Berlin/Heidelberg. ISBN: 978-3-642-25919-7, 978-3-642-25920-3.
DOI: 10.1007/978-3-642-25920-3_4.

In the next decades, practically viable robotic/agent systems are going to be mixed-initiative in nature. Humans will request help from such systems and such systems will request help from humans in achieving the complex mission tasks required. Pragmatically, one requires a distributed task specification language to define tasks and a suitable data structure which satisfies the specification and can be used flexibly by collaborative multi-agent/robotic systems. This paper defines such a task specification language and an abstract data structure called Task Specification Trees which has many of the requisite properties required for mixed-initiative problem solving and adjustable autonomy in a distributed context. A prototype system has been implemented for this delegation framework and has been used practically with collaborative unmanned aircraft systems.

[425] David Landťn, Fredrik Heintz and Patrick Doherty. 2012.
Complex Task Allocation in Mixed-Initiative Delegation: A UAV Case Study.
In Nirmit Desai, Alan Liu, Michael Winikoff, editors, Principles and Practice of Multi-Agent Systems: 13th International Conference, PRIMA 2010, Kolkata, India, November 12-15, 2010, Revised Selected Papers, pages 288–303. In series: Lecture Notes in Computer Science #7057. Springer Berlin/Heidelberg. ISBN: 978-3-642-25919-7, 978-3-642-25920-3.
DOI: 10.1007/978-3-642-25920-3_20.

Unmanned aircraft systems (UASs) are now becoming technologically mature enough to be integrated into civil society. An essential issue is principled mixed-initiative interaction between UASs and human operators. Two central problems are to specify the structure and requirements of complex tasks and to assign platforms to these tasks. We have previously proposed Task Specification Trees (TSTs) as a highly expressive specification language for complex multi-agent tasks that supports mixed-initiative delegation and adjustable autonomy. The main contribution of this paper is a sound and complete distributed heuristic search algorithm for allocating the individual tasks in a TST to platforms. The allocation also instantiates the parameters of the tasks such that all the constraints of the TST are satisfied. Constraints are used to model dependencies between tasks, resource usage as well as temporal and spatial requirements on complex tasks. Finally, we discuss a concrete case study with a team of unmanned aerial vehicles assisting in a challenging emergency situation.

[424] Full text  Cyrille Berger. 2012.
Weak Constraints Network Optimiser.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 1270–1277. IEEE.
DOI: 10.1109/ICRA.2012.6225060.

We present a general framework to estimate the parameters of both a robot and landmarks in 3D. It relies on the use of a stochastic gradient descent method for the optimisation of the nodes in a graph of weak constraints where the landmarks and robot poses are the nodes. Then a belief propagation method combined with covariance intersection is used to estimate the uncertainties of the nodes. The first part of the article describes what is needed to define a constraint and a node models, how those models are used to update the parameters and the uncertainties of the nodes. The second part present the models used for robot poses and interest points, as well as simulation results.

[423] Full text  Gerald Steinbauer and Alexander Kleiner. 2012.
Towards CSP-based mission dispatching in C2/C4I systems.
In Proc. of the IEEE Int. Workshop on Safety, Security and Rescue Robotics (SSRR), pages 1–6. IEEE. ISBN: 978-1-4799-0164-7, 978-1-4799-0163-0, 978-1-4799-0165-4.
DOI: 10.1109/SSRR.2012.6523875.
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

One challenging problem in disaster response is to efficiently assign resources such as fire fighters and trucks to local incidents that are spatially distributed on a map. Existing systems for command and control (C2/C4I) are coming with powerful interfaces enabling the manual assignment of resources to the incident commander. However, with increasing number of local incidents over time the performance of manual methods departs arbitrarily from an optimal solution. In this paper we introduce preliminary results of building an interface between existing professional C2/C4I systems and Constraint Satisfaction Problem (CSP)-solvers. We show by using an example the feasibility of scheduling and assigning missions having deadlines and resource constraints.

[422] L. Marconi, C. Melchiorri, M. Beetz, D. Pangercic, R. Siegwart, S. Leutenegger, R. Carloni, S. Stramigioli, H. Bruyninckx, Patrick Doherty, Alexander Kleiner, V. Lippiello, A. Finzi, B. Siciliano, A. Sala and N. Tomatis. 2012.
The SHERPA project: Smart collaboration between humans and ground-aerial robots for improving rescuing activities in alpine environments.
In Proc. of the IEEE Int. Workshop on Safety, Security and Rescue Robotics (SSRR), pages 1–4. IEEE. ISBN: 978-1-4799-0164-7, 978-1-4799-0163-0, 978-1-4799-0165-4.
DOI: 10.1109/SSRR.2012.6523905.

The goal of the paper is to present the foreseen research activity of the European project ‚ÄúSHERPA‚ÄĚ whose activities will start officially on February 1th 2013. The goal of SHERPA is to develop a mixed ground and aerial robotic platform to support search and rescue activities in a real-world hostile environment, like the alpine scenario that is specifically targeted in the project. Looking into the technological platform and the alpine rescuing scenario, we plan to address a number of research topics about cognition and control. What makes the project potentially very rich from a scientific viewpoint is the heterogeneity and the capabilities to be owned by the different actors of the SHERPA system: the human rescuer is the ‚Äúbusy genius‚ÄĚ, working in team with the ground vehicle, as the ‚Äúintelligent donkey‚ÄĚ, and with the aerial platforms, i.e. the ‚Äútrained wasps‚ÄĚ and ‚Äúpatrolling hawks‚ÄĚ. Indeed, the research activity focuses on how the ‚Äúbusy genius‚ÄĚ and the ‚ÄúSHERPA animals‚ÄĚ interact and collaborate with each other, with their own features and capabilities, toward the achievement of a common goal.

[421] Luc De Raedt, Christian Bessiere, Didier Dubois, Patrick Doherty, Paolo Frasconi, Fredrik Heintz and Peter Lucas. 2012.
Proceedings of the 20th European Conference on Artificial Intelligence (ECAI).
Conference Proceedings. In series: Frontiers in Artificial Intelligence and Applications #242. IOS Press. 1056 pages. ISBN: 978-1-61499-097-0.

[420] Full text  Jonatan Olofsson. 2012.
Towards Autonomous Landing of a Quadrotorusing Monocular SLAM Techniques.
Student Thesis. 102 pages. ISRN: LIU-IDA/LITH-EX-A--12/026--SE.

Use of Unmanned Aerial Vehicles have seen enormous growth in recent years due to the advances in related scientific and technological fields. This fact combined with decreasing costs of using UAVs enables their use in new application areas. Many of these areas are suitable for miniature scale UAVs - Micro Air Vehicles(MAV) - which have the added advantage of portability and ease of deployment. One of the main functionalities necessary for successful MAV deployment in real-world applications is autonomous landing. Landing puts particularly high requirements on positioning accuracy, especially in indoor confined environments where the common global positioning technology is unavailable. For that reason using an additional sensor, such as a camera, is beneficial. In this thesis, a set of technologies for achieving autonomous landing is developed and evaluated. In particular, state estimation based on monocular vision SLAM techniques is fused with data from onboard sensors. This is then used as the basis for nonlinear adaptive control as well trajectory generation for a simple landing procedure. These components are connected using a new proposed framework for robotic development. The proposed system has been fully implemented and tested in a simulated environment and validated using recorded data. Basic autonomous landing was performed in simulation and the result suggests that the proposed system is a viable solution for achieving a fully autonomous landing of a quadrotor.

[419] Full text  Cyrille Berger. 2012.
Toward rich geometric map for SLAM: Online Detection of Planes in 2D LIDAR.
In Proceedings of the International Workshop on Perception for Mobile Robots Autonomy (PEMRA).
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Rich geometric models of the environment are needed for robots to accomplish their missions. However a robot operatingin a large environment would require a compact representation.In this article, we present a method that relies on the idea that a plane appears as a line segment in a 2D scan, andthat by tracking those lines frame after frame, it is possible to estimate the parameters of that plane. The method istherefore divided in three steps: fitting line segments on the points of the 2D scan, tracking those line segments inconsecutive scan and estimating the parameters with a graph based SLAM (Simultaneous Localisation And Mapping)algorithm.

[418] Ha Quang-Thuy, Hoang Thi-Lan-Giao, Linh Anh Nguyen, Hung Son Nguyen, Andrzej Szalas and Tran Thanh-Luong. 2012.
Concept Learning for Description Logic-based Information Systems.
In KSE 2012 - International Conference on Knowledge and Systems Engineering, pages 65–73. IEEE Computer Society.
DOI: 10.1109/KSE.2012.23.

[417] Ha Quang-Thuy, Hoang Thi-Lan-Giao, Linh Anh Nguyen, Nguyen Hung-Son, Andrzej Szalas and Tran Thanh-Luong. 2012.
A Bisimulation-based Method of Concept Learning for Knowledge Bases in Description Logics.
In SoICT 2012 - 3rd International Symposium on Information and Communication Technology, pages 241–249. ACM Press.
DOI: 10.1145/2350716.2350753.

We develop the first bisimulation-based method of concept learning, called BBCL, for knowledge bases in description logics (DLs). Our method is formulated for a large class of useful DLs, with well-known DLs like <em>ALC, SHIQ, SHOIQ, SROIQ</em>. As bisimulation is the notion for characterizing indis-cernibility of objects in DLs, our method is natural and very promising.

[416] Full text  Fredrik Heintz and Tommy Fšrnqvist. 2012.
Pedagogical Experiences of Competitive Elements in an Algorithms Course.
In Proceedings of LTHs 7:e Pedagogiska Inspirationskonferens (PIK).
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

We claim that competitive elements can improve thequality of programming and algorithms courses. To test this, weused our experience from organising national and internationalprogramming competitions to design and evaluate two differentcontests in an introductory algorithms course. The first contestturned lab assignments into a competition, where two groups rancompetitions and two were control groups and did not compete.The second, voluntary, contest, consisting of 15 internationalprogramming competition style problems, was designed tosupport student skill acquisition by providing them withopportunities for deliberate practise. We found that competitiveelements do influence student behaviour and our mainconclusions from the experiment are that students really likecompetitions, that the competition design is very important forthe resulting behaviour of the students, and that active studentsperform better on exams.We also report on an extra-curricular activity in the form of asemester long programming competition as a way of supportingstudent's deliberate practise in computer programming.

[415] Bernhard Nebel and Alexander Kleiner. 2012.
Multi-Agenten-Systeme in der Intralogistik - Erster Teil: Gemeinsam denken.
IEE - Elektrische Automatisierung + Antriebstechnik, -(4):48–53. HŁthig Verlag.
Link to journal: http://www.iee-online.de/2012/

Nicht nur in der Logistik und in der Produktion setzt es sich immer mehr durch, die Steuerung und UŐąberwachung von Aufgaben zu verteilen. FuŐąr eine solche Vorgehens- weise sind sogenannte Multi-Agenten-Systeme (MAS) geeignet, bei denen mehrere ei- genstaŐąndige Systeme miteinander kommunizieren, sich koordinieren und kooperieren. Eine spezielle Form solcher MAS sind Multi-Roboter-Systeme.

[414] Bernhard Nebel and Alexander Kleiner. 2012.
Multi-Agenten-Systeme in der Intralogistik - Zweiter Teil: Effizient transportieren.
IEE - Elektrische Automatisierung + Antriebstechnik, -(5):34–37. HŁthig Verlag.
Link to journal: http://www.iee-online.de/2012/

In der Logisitk, in der Produktion und und in anderen Bereichen setzt es sich immer mehr durch, zentrale Instanzen zu vermeiden und die Steuerung und √úberwachung von Aufgaben zu verteilen. F√ľr eine solche Vorgehensweise sind so genannte Multi-Agenten-Systeme (MAS) ideal geeignet, bei denen mehrere eigenst√§ndige Systeme miteinander kommunizieren, sich koordinieren und kooperieren. Eine spezielle Form solcher MAS sind Multi-Roboter-Systeme, bei denen die einzelnen Agenten sich selbst√§ndig bewegende physikalische Einheiten sind, wie z.B. bei einer Gruppe von Reinigungsrobotern, einem Roboterfu√üballteam oder im Logistiksystem KARIS.

[413] Full text  Patrick Doherty and Fredrik Heintz. 2012.
Delegation-Based Collaboration.
In Proceedings of the 5th International Conference on Cognitive Systems (CogSys).

[412] Barbara Dunin-Keplicz and Andrzej Szalas. 2012.
Epistemic Profiles and Belief Structures.
In Gordan Jezic, Mario Kusek, Ngoc-Thanh Nguyen, Robert J. Howlett, Lakhmi C. Jain, editors, Agent and Multi-Agent Systems. Technologies and Applications: 6th KES International Conference, KES-AMSTA 2012, Dubrovnik, Croatia, June 25-27, 2012. Proceedings, pages 360–369. In series: Lecture Notes in Computer Science #7327. Springer Berlin/Heidelberg. ISBN: 978-3-642-30946-5, 978-3-642-30947-2.
DOI: 10.1007/978-3-642-30947-2_40.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/13481324
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This book constitutes the refereed proceedings of the 6th KES International Conference on Agent and Multi-Agent Systems, KES-AMSTA 2012, held in Dubrovnik, Croatia, in June 2012. &lt;br&gt;The conference attracted a substantial number of researchers and practitioners from all over the world who submitted their papers for ten main tracks covering the methodology and applications of agent and multi-agent systems, one workshop (TRUMAS 2012) and five special sessions on specific topics within the field. The 66 revised papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on virtual organizations, knowledge and learning agents, intelligent workflow, cloud computing and intelligent systems, self-organization, ICT-based alternative and augmentative communication, multi-agent systems, mental and holonic models, assessment methodologies in multi-agent and other paradigms, business processing agents, Trumas 2012 (first international workshop), conversational agents and agent teams, digital economy, and multi-agent systems in distributed environments.

[411] Linh Anh Nguyen and Andrzej Szalas. 2012.
Paraconsistent Reasoning for Semantic Web Agents.
In Ngoc Thanh Nguyen, editor, Transactions on Computational Collective Intelligence VI, pages 36–55. In series: Lecture Notes in Computer Science #7190. Springer Berlin/Heidelberg. ISBN: 978-3-642-29355-9, 978-3-642-29356-6.
DOI: 10.1007/978-3-642-29356-6_2.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/13481193
find book in another country/hitta boken i ett annat land: http://www.worldcat.org/search?q=Transac...

The LNCS journal Transactions on Computational Collective Intelligence (TCCI) focuses on all facets of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems.This, the sixth issue of Transactions on Computational Collective Intelligence contains 10 selected papers, focusing on the topics of classification, agent cooperation, paraconsistent reasoning and agent distributed mobile interaction.

[410] Full text  Anders Hongslo. 2012.
Stream Processing in the Robot Operating System framework.
Student Thesis. 79 pages. ISRN: LIU-IDA/LITH-EX-A--12/030--SE.

Streams of information rather than static databases are becoming increasingly important with the rapid changes involved in a number of fields such as finance, social media and robotics. DyKnow is a stream-based knowledge processing middleware which has been used in autonomous Unmanned Aerial Vehicle (UAV) research. ROS (Robot Operating System) is an open-source robotics framework providing hardware abstraction, device drivers, communication infrastructure, tools, libraries as well as other functionalities.This thesis describes a design and a realization of stream processing in ROS based on the stream-based knowledge processing middleware DyKnow. It describes how relevant information in ROS can be selected, labeled, merged and synchronized to provide streams of states. There are a lot of applications for such stream processing such as execution monitoring or evaluating metric temporal logic formulas through progression over state sequences containing the features of the formulas. Overviews are given of DyKnow and ROS before comparing the two and describing the design. The stream processing capabilities implemented in ROS are demonstrated through performance evaluations which show that such stream processing is fast and efficient. The resulting realization in ROS is also readily extensible to provide further stream processing functionality.

[409] Full text  Viet Ha Nguyen. 2012.
Design Space Exploration of the Quality of Service for Stream Reasoning Applications.
Student Thesis. 35 pages. ISRN: LIU-IDA/LITH-EX-A--12/027--SE.

An Unmanned Aerial Vehicle (UAV) is often an aircraft with no crew that can fly independently by a preprogrammed plan, or by remote control. Several UAV applications, like autonomously surveillance and traffic monitoring, are real-time applications. Hence tasks in these applications must complete within specied deadlines.Real Time Calculus (RTC) is a formal framework for reasoning about realtime systems and in particular streaming applications. RTC has its mathematical roots in Network Calculus. It supports timing analysis, estimating loads and predicting memory requirements.In this thesis, a formal analysis of real-time stream reasoning for UAV applications is conducted. The performance analysis is based on RTC using an abstract performance model of the streaming reasoning on board a UAV. In this study, we consider two dierent scheduling methods, first-in-first-out (FIFO) and fixed priority (FP). In the FIFO scheduling model the priorities of the tasks are assigned and processed based on the order of their arrival, while in the FP scheduling model the priorities of the tasks are preassigned. The Quality of Service (QoS) of these applications is calculated and analyzed in a proposed design space exploration framework.QoS can be defined dierently depending on what field we are studying and in this thesis we are interested in studying the delays of the real-time stream reasoning applications when (i) we fix jitters and number of instances and vary the periods, (ii) we fix the periods and number of instances and vary the jitters, and (iii) we fix the periods, jitters and vary the number of instances.

[408] Full text  Fredrik Heintz and Zlatan Dragisic. 2012.
Semantic Information Integration for Stream Reasoning.
In Proceedings of the 15th International Conference on Information Fusion (FUSION). LinkŲping University Electronic Press.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

The main contribution of this paper is a practicalsemantic information integration approach for stream reasoningbased on semantic matching. This is an important functionality for situation awareness applications where temporal reasoning over streams from distributed sources is needed. The integration is achieved by creating a common ontology, specifying the semantic content of streams relative to the ontology and then use semantic matching to find relevant streams. By using semantic mappings between ontologies it is also possible to do semantic matching over multiple ontologies. The complete stream reasoning approach is integrated in the Robot Operating System(ROS) and used in collaborative unmanned aircraft systems missions.

[407] Anna PernestŚl, Mattias Nyberg and HŚkan Warnquist. 2012.
Modeling and inference for troubleshooting with interventions applied to a heavy truck auxiliary braking system.
Engineering applications of artificial intelligence, 25(4):705–719. Elsevier.
DOI: 10.1016/j.engappai.2011.02.018.

Computer assisted troubleshooting with external interventions is considered. The work is motivated by the task of repairing an automotive vehicle at lowest possible expected cost. The main contribution is a decision theoretic troubleshooting system that is developed to handle external interventions. In particular, practical issues in modeling for troubleshooting are discussed, the troubleshooting system is described, and a method for the efficient probability computations is developed. The troubleshooting systems consists of two parts; a planner that relies on AO* search and a diagnoser that utilizes Bayesian networks (BN). The work is based on a case study of an auxiliary braking system of a modern truck. Two main challenges in troubleshooting automotive vehicles are the need for disassembling the vehicle during troubleshooting to access parts to repair, and the difficulty to verify that the vehicle is fault free. These facts lead to that probabilities for faults and for future observations must be computed for a system that has been subject to external interventions that cause changes in the dependency structure. The probability computations are further complicated due to the mixture of instantaneous and non-instantaneous dependencies. To compute the probabilities, we develop a method based on an algorithm, updateBN, that updates a static BN to account for the external interventions.

[406] Full text  Erik Sandewall. 2012.
Maintaining Live Discussion in Two-Stage Open Peer Review.
Frontiers in Computational Neuroscience, 6(9):????. Frontiers Research Foundation.
DOI: 10.3389/fncom.2012.00009.
Note: funding agencies|Knut and Alice Wallenberg Foundation||
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Open peer review has been proposed for a number of reasons, in particular, for increasing the transparency of the article selection process for a journal, and for obtaining a broader basis for feedback to the authors and for the acceptance decision. The review discussion may also in itself have a value for the research community. These goals rely on the existence of a lively review discussion, but several experiments with open-process peer review in recent years have encountered the problem of faltering review discussions. The present article addresses the question of how lively review discussion may be fostered by relating the experience of the journal Electronic Transactions on Artificial Intelligence (ETAI) which was an early experiment with open peer review. Factors influencing the discussion activity are identified. It is observed that it is more difficult to obtain lively discussion when the number of contributed articles increases, which implies difficulties for scaling up the open peer review model. Suggestions are made for how this difficulty may be overcome.

[405] Full text  Daniel Lazarovski. 2012.
Extending the Stream Reasoning in DyKnow with Spatial Reasoning in RCC-8.
Student Thesis. 74 pages. ISRN: LIU-IDA/LITH-EX-A--12/008--SE.

Autonomous systems require a lot of information about the environment in which they operate in order to perform different high-level tasks. The information is made available through various sources, such as remote and on-board sensors, databases, GIS, the Internet, etc. The sensory input especially is incrementally available to the systems and can be represented as streams. High-level tasks often require some sort of reasoning over the input data, however raw streaming input is often not suitable for the higher level representations needed for reasoning. DyKnow is a stream processing framework that provides functionalities to represent knowledge needed for reasoning from streaming inputs. DyKnow has been used within a platform for task planning and execution monitoring for UAVs. The execution monitoring is performed using formula progression with monitor rules specified as temporal logic formulas. In this thesis we present an analysis for providing spatio-temporal functionalities to the formula progressor and we extend the formula progression with spatial reasoning in RCC-8. The result implementation is capable of evaluating spatio-temporal logic formulas using progression over streaming data. In addition, a ROS implementation of the formula progressor is presented as a part of a spatio-temporal stream reasoning architecture in ROS.

[404] Full text  Barbara Dunin-Keplicz and Andrzej Szalas. 2012.
Agents in Approximate Environments.
In Jan Ejick and Rineke Verbrugge, editors, Games, Actions and Social Software: Multidisciplinary Aspects, pages 141–163. In series: Lecture Notes in Computer Science #7010. Springer. ISBN: 978-3-642-29325-2, 978-3-642-29326-9.
DOI: 10.1007/978-3-642-29326-9_8.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/13428777
find book in another country/hitta boken i ett annat land: http://www.worldcat.org/search?q=Games%2...

Edited in collaboration with FoLLI, the Association of Logic, Language and Information, this book collects a set of chapters of the multi-disciplinary project \"Games, actions and Social software\" which was carried out at the Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NIAS) in Wassenaar, from September 2006 through January 2007.&lt;br&gt;The chapters focus on social software and the social sciences, knowledge, belief and action, perception, communication, and cooperation.

[403] Full text  Patrick Doherty, Jonas KvarnstrŲm and Andrzej Szalas. 2012.
Temporal Composite Actions with Constraints.
In Proceedings of the 13th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 478–488. AAAI Press. ISBN: 978-1-57735-560-1, 978-1-57735-561-8.
Link: http://www.aaai.org/ocs/index.php/KR/KR1...

Complex mission or task specification languages play a fundamentally important role in human/robotic interaction. In realistic scenarios such as emergency response, specifying temporal, resource and other constraints on a mission is an essential component due to the dynamic and contingent nature of the operational environments. It is also desirable that in addition to having a formal semantics, the language should be sufficiently expressive, pragmatic and abstract. The main goal of this paper is to propose a mission specification language that meets these requirements. It is based on extending both the syntax and semantics of a well-established formalism for reasoning about action and change, Temporal Action Logic (TAL), in order to represent temporal composite actions with constraints. Fixpoints are required to specify loops and recursion in the extended language. The results include a sound and complete proof theory for this extension. To ensure that the composite language constructs are adequately grounded in the pragmatic operation of robotic systems, Task Specification Trees (TSTs) and their mapping to these constructs are proposed. The expressive and pragmatic adequacy of this approach is demonstrated using an emergency response scenario.

2011
[402] Full text  Gianpaolo Conte and Patrick Doherty. 2011.
A Visual Navigation System for UAS Based on Geo-referenced Imagery.
In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII-1/C22Proceedings of the International Conference on Unmanned Aerial Vehicle in Geomatics, Zurich, Switzerland, September 14-16, 2011. In series: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences #??.

[401] Full text  Jonas KvarnstrŲm. 2011.
Planning for Loosely Coupled Agents Using Partial Order Forward-Chaining.
In Fahiem Bacchus, Carmel Domshlak, Stefan Edelkamp, Malte Helmert, editors, Proceedings of the 21st International Conference on Automated Planning and Scheduling (ICAPS), pages 138–145. AAAI Press. ISBN: 978-1-57735-503-8, 978-1-57735-504-5.
Fulltext: http://www.aaai.org/ocs/index.php/ICAPS/...

We investigate a hybrid between temporal partial-order and forward-chaining planning where each action in a partially ordered plan is associated with a partially defined state. The focus is on centralized planning for multi-agent domains and on loose commitment to the precedence between actions belonging to distinct agents, leading to execution schedules that are flexible where it matters the most. Each agent, on the other hand, has a sequential thread of execution reminiscent of forward-chaining. This results in strong and informative agent-specific partial states that can be used for partial evaluation of preconditions as well as precondition control formulas used as guidance. Empirical evaluation shows the resulting planner to be competitive with TLplan and TALplanner, two other planners based on control formulas, while using a considerably more expressive and flexible plan structure.

[400] Full text  Teresa Vidal-Calleja, Cyrille Berger, Joan Solŗ and Simon Lacroix. 2011.
Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain.
Robotics and Autonomous Systems, 59(9):654–674. Elsevier.
DOI: 10.1016/j.robot.2011.05.008.

This paper addresses the cooperative localization and visual mapping problem with multiple heterogeneous robots. The approach is designed to deal with the challenging large semi-structured outdoors environments in which aerial/ground ensembles are to evolve. We propose the use of heterogeneous visual landmarks, points and line segments, to achieve effective cooperation in such environments. A large-scale SLAM algorithm is generalized to handle multiple robots, in which a global graph maintains the relative relationships between a series of local sub-maps built by the different robots. The key issue when dealing with multiple robots is to find the link between them, and to integrate these relations to maintain the overall geometric consistency; the events that introduce these links on the global graph are described in detail. Monocular cameras are considered as the primary extereoceptive sensor. In order to achieve the undelayed initialization required by the bearing-only observations, the well-known inverse-depth parametrization is adopted to estimate 3D points. Similarly, to estimate 3D line segments, we present a novel parametrization based on anchored Pl√ľcker coordinates, to which extensible endpoints are added. Extensive simulations show the proposed developments, and the overall approach is illustrated using real-data taken with a helicopter and a ground rover.

[399] Full text  Patrick Doherty, Fredrik Heintz and David Landťn. 2011.
A Delegation-Based Collaborative Robotic Framework.
In Christian Guttmann, editor, Proceedings of the 3rd International Workshop on Collaborative Agents - Research and development.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

[398] Anders Kofod-Peteresen, Fredrik Heintz and Langseth Helge. 2011.
Elevent Scandinavian Conference on Artifical Intelligence SCAI 2011.
Conference Proceedings. In series: Frontiers in Artificial Intelligence and Applications #227. IOS Press. 197 pages. ISBN: 978-1-60750-753-6.

[397] Full text  Patrick Doherty, Fredrik Heintz and David Landťn. 2011.
A Delegation-Based Architecture for Collaborative Robotics.
In Danny Weyns and Marie-Pierre Gleizes, editors, Agent-Oriented Software Engineering XI: 11th International Workshop, AOSE 2010, Toronto, Canada, May 10-11, 2010, Revised Selected Papers, pages 205–247. In series: Lecture Notes in Computer Science #6788. Springer Berlin/Heidelberg. ISBN: 978-3-642-22635-9.
DOI: 10.1007/978-3-642-22636-6_13.
Find book in another country/Hitta boken i ett annat land: http://www.worldcat.org/search?q=978-3-6...
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/12509689
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Collaborative robotic systems have much to gain by leveraging results from the area of multi-agent systems and in particular agent-oriented software engineering. Agent-oriented software engineering has much to gain by using collaborative robotic systems as a testbed. In this article, we propose and specify a formally grounded generic collaborative system shell for robotic systems and human operated ground control systems. Collaboration is formalized in terms of the concept of delegation and delegation is instantiated as a speech act. Task Specification Trees are introduced as both a formal and pragmatic characterization of tasks and tasks are recursively delegated through a delegation process implemented in the collaborative system shell. The delegation speech act is formally grounded in the implementation using Task Specification Trees, task allocation via auctions and distributed constraint problem solving. The system is implemented as a prototype on Unmanned Aerial Vehicle systems and a case study targeting emergency service applications is presented.

[396] Full text  Patrick Doherty and Fredrik Heintz. 2011.
A Delegation-Based Cooperative Robotic Framework.
In Proceedings of the IEEE International Conference on Robotics and Biomimetic, pages 2955–2962. IEEE conference proceedings. ISBN: 978-1-4577-2136-6.
DOI: 10.1109/ROBIO.2011.6181755.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Cooperative robotic systems, such as unmanned aircraft systems, are becoming technologically mature enough to be integrated into civil society. To gain practical use and acceptance, a verifiable, principled and well-defined foundation for interactions between human operators and autonomous systems is needed. In this paper, we propose and specify such a formally grounded collaboration framework. Collaboration is formalized in terms of the concept of delegation and delegation is instantiated as a speech act. Task Specification Trees are introduced as both a formal and pragmatic characterization of tasks and tasks are recursively delegated through a delegation process. The delegation speech act is formally grounded in the implementation using Task Specification Trees, task allocation via auctions and distributed constraint solving. The system is implemented as a prototype on unmanned aerial vehicle systems and a case study targeting emergency service applications is presented.

[395] Jan Maluszynski and Andrzej Szalas. 2011.
Living with Inconsistency and Taming Nonmonotonicity.
In O. de Moor, G. Gottlob, T. Furche, A. Sellers, editors, Datalog Reloaded, pages 334–398. In series: Lecture Notes in Computer Science #6702. Springer Berlin/Heidelberg. ISBN: 978-3-642-24205-2.
DOI: 10.1007/978-3-642-24206-9_22.

In this paper we consider rule-based query languages with negation inbodies and heads of rules, traditionally denoted by DATALOG--. Tractable andat the same time intuitive semantics for DATALOG-- has not been provided evenif the area of deductive databases is over 30 years old. In this paper we identifysources of the problem and propose a query language, which we call 4QL.The 4QL language supports a modular and layered architecture and providesa tractable framework for many forms of rule-based reasoning both monotonicand nonmonotonic. As the underpinning principle we assume openness of theworld, which may lead to the lack of knowledge. Negation in rule heads may leadto inconsistencies. To reduce the unknown/inconsistent zones we introduce simpleconstructs which provide means for application-specific disambiguation ofinconsistent information, the use of Local Closed World Assumption (thus alsoClosed World Assumption, if needed), as well as various forms of default anddefeasible reasoning.

[394] Son Thanh Cao, Linh Anh Nguyen and Andrzej Szalas. 2011.
WORL: A Web Ontology Rule Language.
In Proceedings of the 3rd International Conference on Knowledge and Systems Engineering (KSE), pages 32–39. IEEE. ISBN: 978-1-4577-1848-9.
DOI: 10.1109/KSE.2011.14.

We develop a Web ontology rule language, called WORL, which combines a variant of OWL 2 RL with eDatalog-with-negation. We disallow the features of OWL 2 RL that play the role of constraints (i.e., the ones that are translated to negative clauses), but allow additional features like negation, the minimal number restriction and unary external checkable predicates to occur in the left hand side of concept inclusion axioms. Some restrictions are adopted to guarantee a translation into eDatalog-with-negation. We also develop the well-founded semantics for WORL and the standard semantics for stratified WORL (SWORL) via translation into eDatalog-with-negation. Both WORL and SWORL have PTime data complexity. In contrast to the existing combined formalisms, in WORL and SWORL negation in concept inclusion axioms is interpreted using nonmonotonic semantics.

[393] Patrick Doherty, Barbara Dunin-Keplicz and Andrzej Szalas. 2011.
Tractable model checking for fragments of higher-order coalition logic.
In Liz Sonenberg, Peter Stone, Kagan Tumer, Pinar Yolum, editors, Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2, pages 743–750. AAAI Press. ISBN: 0-9826571-6-1, 978-0-9826571-6-4.
Link: http://dl.acm.org/citation.cfm?id=203172...

A number of popular logical formalisms for representing and reasoning about the abilities of teams or coalitions of agents have been proposed beginning with the Coalition Logic (CL) of Pauly. √Ögotnes et al introduced a means of succinctly expressing quantification over coalitions without compromising the computational complexity of model checking in CL by introducing Quantified Coalition Logic (QCL). QCL introduces a separate logical language for characterizing coalitions in the modal operators used in QCL. Boella et al, increased the representational expressibility of such formalisms by introducing Higher-Order Coalition Logic (HCL), a monadic second-order logic with special set grouping operators. Tractable fragments of HCL suitable for efficient model checking have yet to be identified. In this paper, we relax the monadic restriction used in HCL and restrict ourselves to the diamond operator. We show how formulas using the diamond operator are logically equivalent to second-order formulas. This permits us to isolate and define well-behaved expressive fragments of second-order logic amenable to model-checking in PTime. To do this, we appeal to techniques used in deductive databases and quantifier elimination. In addition, we take advantage of the monotonicity of the effectivity function resulting in exponentially more succinct representation of models. The net result is identification of highly expressible fragments of a generalized HCL where model checking can be done efficiently in PTime.

[392] Son Thanh Cao, Anh Linh Nguyen and Andrzej Szalas. 2011.
On the Web Ontology Rule Language OWL 2 RL.
In Piotr Jedrzejowicz, Ngoc Thanh Nguyen and Kiem Hoang, editors, Proceedings of the 3rd International Conference on Computational Collective Intelligence, Technologies and Applications (ICCCI), pages 254–264. In series: Lecture Notes in Computer Science #6922. Springer Berlin/Heidelberg. ISBN: 978-3-642-23934-2.
DOI: 10.1007/978-3-642-23935-9_25.

It is known that the OWL 2 RL Web Ontology Language Profile has PTime data complexity and can be translated into Datalog. However, a knowledge base in OWL 2 RL may be unsatisfiable. The reason is that, when translated into Datalog, the result may consist of a Datalog program and a set of constraints in the form of negative clauses. In this paper we first identify a maximal fragment of OWL 2 RL called OWL 2 RL<sup>‚ÄČ+‚ÄČ</sup>with the property that every knowledge base expressed in this fragment can be translated into a Datalog program and hence is satisfiable. We then propose some extensions of OWL 2 RL and OWL 2 RL<sup>‚ÄČ+‚ÄČ</sup> that still have PTime data complexity.

[391] Full text  Patrick Doherty, Tomasz Michalak, Jacek Sroka and Andrzej Szalas. 2011.
Contextual Coalitional Games.
In Mohua Banerjee, Anil Seth, editors, Proceedings of the 4th Indian Conference on Logic and its Applications (ICLA), pages 65–78. In series: Lecture Notes in Artificial Intelligence #6521. Springer Berlin/Heidelberg.
DOI: 10.1007/978-3-642-18026-2_7.

The study of cooperation among agents is of central interest in multi-agent systems research. A popular way to model cooperation is through coalitional game theory. Much research in this area has had limited practical applicability as regards real-world multi-agent systems due to the fact that it assumes<em>deterministic</em> payoffs to coalitions and in addition does not apply to multi-agent environments that are<em>stochastic</em> in nature. In this paper, we propose a novel approach to modeling such scenarios where coalitional games will be contextualized through the use of logical expressions representing environmental and other state, and probability distributions will be placed on the space of contexts in order to model the stochastic nature of the scenarios. More formally, we present a formal representation language for representing contextualized coalitional games embedded in stochastic environments and we define and show how to compute <em>expected Shapley values</em> in such games in a computationally efficient manner. We present the value of the approach through an example involving robotics assistance in emergencies.

[390] Barbara Dunin-Keplicz, Anh Linh Nguyen and Andrzej Szalas. 2011.
Converse-PDL with Regular Inclusion Axioms: A Framework for MAS Logics.
Journal of Applied Non-Classical Logics, 21(1):61–91. Lavoisier.
DOI: 10.3166/JANCL.21.61-91.

<em>In this paper we study automated reasoning in the modal logic CPDLreg which is a combination of CPDL (Propositional Dynamic Logic with Converse) and REGc (Regular Grammar Logic with Converse). The logic CPDL is widely used in many areas, including program verification, theory of action and change, and knowledge representation. On the other hand, the logic REGc is applicable in reasoning about epistemic states and ontologies (via Description Logics). The modal logic CPDLreg can serve as a technical foundation for reasoning about agency. Even very rich multi-agent logics can be embedded into CPDLreg via a suitable translation. Therefore, CPDLreg can serve as a test bed to implement and possibly verify new ideas without providing specific automated reasoning techniques for the logic in question. This process can to a large extent be automated. The idea of embedding various logics into CPDLreg is illustrated on a rather advanced logic TEAMLOGK designed to specify teamwork in multi-agent systems. Apart from defining informational and motivational attitudes of groups of agents, TEAMLOGK allows for grading agents' beliefs, goals and intentions. The current paper is a companion to our paper (Dunin-Kńôplicz et al., 2010a). The main contribution are proofs of soundness and completeness of the tableau calculus for CPDLreg provided in (Dunin-Kńôplicz et al., 2010a).</em>

[389] Linh Anh Nguyen and Andrzej Szalas. 2011.
ExpTime Tableau Decision Procedures for Regular Grammar Logics with Converse.
Studia Logica: An International Journal for Symbolic Logic, 98(3):387–428. Springer Berlin/Heidelberg.
DOI: 10.1007/s11225-011-9341-3.

Grammar logics were introduced by Fari√Īas del Cerro and Penttonen in 1988 and have been widely studied. In this paper we consider regular grammar logics with converse (<em>REG</em> <sup><em>c</em> </sup>logics) and present sound and complete tableau calculi for the general satisfiability problem of <em>REG</em> <sup><em>c</em> </sup>logics and the problem of checking consistency of an ABox w.r.t. a TBox in a <em>REG</em> <sup><em>c</em> </sup>logic. Using our calculi we develop ExpTime (optimal) tableau decision procedures for the mentioned problems, to which various optimization techniques can be applied. We also prove a new result that the data complexity of the instance checking problem in <em>REG</em> <sup><em>c</em></sup>logics is coNP-complete.

[388] Jan Maluszynski and Andrzej Szalas. 2011.
Logical Foundations and Complexity of 4QL, a Query Language with Unrestricted Negation.
Journal of Applied Non-Classical Logics, 21(2):211–232. Lavoisier.
DOI: 10.3166/JANCL.21.211-232.

The paper discusses properties of 4QL, a DATALOG¬¨¬¨-like query language, originally outlined by MaŇāuszy¬īnski and SzaŇāas (MaŇāuszy¬īnski &amp; SzaŇāas, 2011). 4QL allows one to use rules with negation in heads and bodies of rules. It is based on a simple and intuitive semantics and provides uniform tools for ‚Äúlightweight‚ÄĚ versions of known forms of nonmonotonic reasoning. Negated literals in heads of rules may naturally lead to inconsistencies. On the other hand, rules do not have to attach meaning to some literals. Therefore 4QL is founded on a four-valued semantics, employing the logic introduced in (MaŇāuszy¬īnski et al., 2008; Vit√≥ria et al., 2009) with truth values: ‚Äėtrue‚Äô, ‚Äėfalse‚Äô, ‚Äėinconsistent‚Äô and ‚Äėunknown‚Äô. In addition, 4QL is tractable w.r.t. data complexity and captures PTIME queries. Even though DATALOG¬¨¬¨ is known as a concept for the last 30 years, to our best knowledge no existing approach enjoys these properties. In the current paper we:<ul><li>investigate properties of well-supported models of 4QL</li><li>prove the correctness of the algorithm for computing well-supported models</li><li>show that 4QL has PTIME data complexity and captures PTIME.</li></ul>

[387] Full text  Zlatan Dragisic. 2011.
Semantic Matching for Stream Reasoning.
Student Thesis. 110 pages. ISRN: LIU-IDA/LITH-EX-A--11/041--SE.

Autonomous system needs to do a great deal of reasoning during execution in order to provide timely reactions to changes in their environment. Data needed for this reasoning process is often provided through a number of sensors. One approach for this kind of reasoning is evaluation of temporal logical formulas through progression. To evaluate these formulas it is necessary to provide relevant data for each symbol in a formula. Mapping relevant data to symbols in a formula could be done manually, however as systems become more complex it is harder for a designer to explicitly state and maintain thismapping. Therefore, automatic support for mapping data from sensors to symbols would make system more flexible and easier to maintain.DyKnow is a knowledge processing middleware which provides the support for processing data on different levels of abstractions. The output from the processing components in DyKnow is in the form of streams of information. In the case of DyKnow, reasoning over incrementally available data is done by progressing metric temporal logical formulas. A logical formula contains a number of symbols whose values over time must be collected and synchronized in order to determine the truth value of the formula. Mapping symbols in formula to relevant streams is done manually in DyKnow. The purpose of this matching is for each variable to find one or more streams whose content matches the intended meaning of the variable.This thesis analyses and provides a solution to the process of semantic matching. The analysis is mostly focused on how the existing semantic technologies such as ontologies can be used in this process. The thesis also analyses how this process can be used for matching symbols in a formula to content of streams on distributed and heterogeneous platforms. Finally, the thesis presents an implementation in the Robot Operating System (ROS). The implementation is tested in two case studies which cover a scenario where there is only a single platform in a system and a scenario where there are multiple distributed heterogeneous platforms in a system.The conclusions are that the semantic matching represents an important step towards fully automatized semantic-based stream reasoning. Our solution also shows that semantic technologies are suitable for establishing machine-readable domain models. The use of these technologies made the semantic matching domain and platform independent as all domain and platform specific knowledge is specified in ontologies. Moreover, semantic technologies provide support for integration of data from heterogeneous sources which makes it possible for platforms to use streams from distributed sources.

[386] Mark Buller, Paul Cuddihy, Ernest Davis, Patrick Doherty, Finale Doshi-Velez, Esra Erdem, Douglas Fisher, Nancy Green, Knut Hinkelmann, James McLurkin, Mary Lou Maher, Rajiv Maheswaran, Sara Rubinelli, Nathan Schurr, Donia Scott, Dylan Shell, Pedro Szekely, Barbara Thoenssen and Arnold B Urken. 2011.
Reports of the AAAI 2011 Spring Symposia.
The AI Magazine, 32(3):119–127. AAAI Press.

The Association for the Advancement of Artificial Intelligence presented the 2011 Spring Symposium Series Monday through Wednesday, March 21-23, 2011, at Stanford University. This report summarizes the eight symposia.

[385] Full text  Piotr Rudol. 2011.
Increasing Autonomy of Unmanned Aircraft Systems Through the Use of Imaging Sensors.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1510. LinkŲping University Electronic Press. 96 pages. ISBN: 9789173930345.
cover: http://liu.diva-portal.org/smash/get/div...

The range of missions performed by Unmanned Aircraft Systems (UAS) has been steadily growing in the past decades thanks to continued development in several disciplines. The goal of increasing the autonomy of UAS's is widening the range of tasks which can be carried out without, or with minimal, external help. This thesis presents methods for increasing specific aspects of autonomy of UAS's operating both in outdoor and indoor environments where cameras are used as the primary sensors.First, a method for fusing color and thermal images for object detection, geolocation and tracking for UAS's operating primarily outdoors is presented. Specifically, a method for building saliency maps where human body locations are marked as points of interest is described. Such maps can be used in emergency situations to increase the situational awareness of first responders or a robotic system itself. Additionally, the same method is applied to the problem of vehicle tracking. A generated stream of geographical locations of tracked vehicles increases situational awareness by allowing for qualitative reasoning about, for example, vehicles overtaking, entering or leaving crossings.Second, two approaches to the UAS indoor localization problem in the absence of GPS-based positioning are presented. Both use cameras as the main sensors and enable autonomous indoor ight and navigation. The first approach takes advantage of cooperation with a ground robot to provide a UAS with its localization information. The second approach uses marker-based visual pose estimation where all computations are done onboard a small-scale aircraft which additionally increases its autonomy by not relying on external computational power.

[384] Full text  Mariusz Wzorek. 2011.
Selected Aspects of Navigation and Path Planning in Unmanned Aircraft Systems.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1509. LinkŲping University Electronic Press. 108 pages. ISBN: 9789173930376.
cover: http://liu.diva-portal.org/smash/get/div...

Unmanned aircraft systems (UASs) are an important future technology with early generations already being used in many areas of application encompassing both military and civilian domains. This thesis proposes a number of integration techniques for combining control-based navigation with more abstract path planning functionality for UASs. These techniques are empirically tested and validated using an RMAX helicopter platform used in the UASTechLab at Linköping University. Although the thesis focuses on helicopter platforms, the techniques are generic in nature and can be used in other robotic systems.At the control level a navigation task is executed by a set of control modes. A framework based on the abstraction of hierarchical concurrent state machines for the design and development of hybrid control systems is presented. The framework is used to specify reactive behaviors and for sequentialisation of control modes. Selected examples of control systems deployed on UASs are presented. Collision-free paths executed at the control level are generated by path planning algorithms.We propose a path replanning framework extending the existing path planners to allow dynamic repair of flight paths when new obstacles or no-fly zones obstructing the current flight path are detected. Additionally, a novel approach to selecting the best path repair strategy based on machine learning technique is presented. A prerequisite for a safe navigation in a real-world environment is an accurate geometrical model. As a step towards building accurate 3D models onboard UASs initial work on the integration of a laser range finder with a helicopter platform is also presented.Combination of the techniques presented provides another step towards building comprehensive and robust navigation systems for future UASs.

[383] Full text  David Landťn. 2011.
Complex Task Allocation for Delegation: From Theory to Practice.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1506. LinkŲping University Electronic Press. 140 pages. ISBN: 9789173930482.
cover: http://liu.diva-portal.org/smash/get/div...

The problem of determining who should do what given a set of tasks and a set of agents is called the task allocation problem. The problem occurs in many multi-agent system applications where a workload of tasks should be shared by a number of agents. In our case, the task allocation problem occurs as an integral part of a larger problem of determining if a task can be delegated from one agent to another.Delegation is the act of handing over the responsibility for something to someone. Previously, a theory for delegation including a delegation speech act has been specified. The speech act specifies the preconditions that must be fulfilled before the delegation can be carried out, and the postconditions that will be true afterward. To actually use the speech act in a multi-agent system, there must be a practical way of determining if the preconditions are true. This can be done by a process that includes solving a complex task allocation problem by the agents involved in the delegation.In this thesis a constraint-based task specification formalism, a complex task allocation algorithm for allocating tasks to unmanned aerial vehicles and a generic collaborative system shell for robotic systems are developed. The three components are used as the basis for a collaborative unmanned aircraft system that uses delegation for distributing and coordinating the agents' execution of complex tasks.

[382] Full text  Marjan Alirezaie. 2011.
Semantic Analysis Of Multi Meaning Words Using Machine Learning And Knowledge Representation.
Student Thesis. 74 pages. ISRN: LiU/IDA-EX-A- -11/011- -SE.

The present thesis addresses machine learning in a domain of naturallanguage phrases that are names of universities. It describes two approaches to this problem and a software implementation that has made it possible to evaluate them and to compare them.In general terms, the system's task is to learn to 'understand' the significance of the various components of a university name, such as the city or region where the university is located, the scienti c disciplines that are studied there, or the name of a famous person which may be part of the university name. A concrete test for whether the system has acquired this understanding is when it is able to compose a plausible university name given some components that should occur in the name.In order to achieve this capability, our system learns the structure of available names of some universities in a given data set, i.e. it acquires a grammar for the microlanguage of university names. One of the challenges is that the system may encounter ambiguities due to multi meaning words. This problem is addressed using a small ontology that is created during the training phase.Both domain knowledge and grammatical knowledge is represented using decision trees, which is an ecient method for concept learning. Besides for inductive inference, their role is to partition the data set into a hierarchical structure which is used for resolving ambiguities.The present report also de nes some modi cations in the de nitions of parameters, for example a parameter for entropy, which enable the system to deal with cognitive uncertainties. Our method for automatic syntax acquisition, ADIOS, is an unsupervised learning method. This method is described and discussed here, including a report on the outcome of the tests using our data set.The software that has been implemented and used in this project has been implemented in C.

[381] Full text  HŚkan Warnquist. 2011.
Computer-Assisted Troubleshooting for Efficient Off-board Diagnosis.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1490. LinkŲping University Electronic Press. 169 pages. ISBN: 9789173931519.
cover: http://liu.diva-portal.org/smash/get/div...

This licentiate thesis considers computer-assisted troubleshooting of complex products such as heavy trucks. The troubleshooting task is to find and repair all faulty components in a malfunctioning system. This is done by performing actions to gather more information regarding which faults there can be or to repair components that are suspected to be faulty. The expected cost of the performed actions should be as low as possible.The work described in this thesis contributes to solving the troubleshooting task in such a way that a good trade-off between computation time and solution quality can be made. A framework for troubleshooting is developed where the system is diagnosed using non-stationary dynamic Bayesian networks and the decisions of which actions to perform are made using a new planning algorithm for Stochastic Shortest Path Problems called Iterative Bounding LAO*.It is shown how the troubleshooting problem can be converted into a Stochastic Shortest Path problem so that it can be efficiently solved using general algorithms such as Iterative Bounding LAO*. New and improved search heuristics for solving the troubleshooting problem by searching are also presented in this thesis.The methods presented in this thesis are evaluated in a case study of an auxiliary hydraulic braking system of a modern truck. The evaluation shows that the new algorithm Iterative Bounding LAO* creates troubleshooting plans with a lower expected cost faster than existing state-of-the-art algorithms in the literature. The case study shows that the troubleshooting framework can be applied to systems from the heavy vehicles domain.

[380] Full text  Per-Magnus Olsson. 2011.
Positioning Algorithms for Surveillance Using Unmanned Aerial Vehicles.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1476. LinkŲping University Electronic Press. 140 pages. ISBN: 9789173932004.
cover: http://liu.diva-portal.org/smash/get/div...

Surveillance is an important application for unmanned aerial vehicles (UAVs). The sensed information often has high priority and it must be made available to human operators as quickly as possible. Due to obstacles and limited communication range, it is not always possible to transmit the information directly to the base station. In this case, other UAVs can form a relay chain between the surveillance UAV and the base station. Determining suitable positions for such UAVs is a complex optimization problem in and of itself, and is made even more diÔ¨Écult by communication and surveillance constraints.To solve diÔ¨Äerent variations of Ô¨Ānding positions for UAVs for surveillance of one target, two new algorithms have been developed. One of the algorithms is developed especially for Ô¨Ānding a set of relay chains oÔ¨Äering diÔ¨Äerent trade-oÔ¨Äs between the number of UAVsand the quality of the chain. The other algorithm is tailored towards Ô¨Ānding the highest quality chain possible, given a limited number of available UAVs.Finding the optimal positions for surveillance of several targets is more diÔ¨Écult. A study has been performed, in order to determine how the problems of interest can besolved. It turns out that very few of the existing algorithms can be used due to the characteristics of our speciÔ¨Āc problem. For this reason, an algorithm for quickly calculating positions for surveillance of multiple targets has been developed. This enables calculation of an initial chain that is immediately made available to the user, and the chain is then incrementally optimized according to the user‚Äôs desire.

[379] Full text  Erik Sandewall. 2011.
From systems to logic in the early development of nonmonotonic reasoning.
Artificial Intelligence, 175(1):416–427. Elsevier.
DOI: 10.1016/j.artint.2010.04.013.

This note describes how the notion of nonmonotonic reasoning emerged in Artificial Intelligence from the mid-1960s to 1980. It gives particular attention to the interplay between three kinds of activities: design of high-level programming systems for AI, design of truth-maintenance systems, and the development of nonmonotonic logics. This was not merely a development from logic to implementation: in several cases there was a development from a system design to a corresponding logic. The article concludes with some reflections on the roles and relationships between logicist theory and system design in AI, and in particular in Knowledge Representation.

2010
[378] Full text  Erik Sandewall. 2010.
Exercising Moral Copyright for Evolving Publications.
ScieCom Info, 6(3):????. Svenskt Resurscentrum fŲr Vetenskaplig Kommunikation.
Link: http://www.sciecom.org/ojs/index.php/sci...

[377] Barbara Dunin-Keplicz, Anh Linh Nguyen and Andrzej Szalas. 2010.
Graded Beliefs, Goals and Intentions.
In Proceedings of the 3rd Workshop on Logical Aspects of Multi-Agent Systems (LAMAS), pages 1–15. AAAI Press.

[376] Cyrille Berger and Simon Lacroix. 2010.
DSeg: Dťtection directe de segments dans une image.
In 17Ťme congrŤs francophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA).

Cet article présente une approche ``model-driven'' pour détecter des segmentsde droite dans une image. L'approche détecte les segments de manièreincrémentale sur la base du gradient de l'image, en exploitant un filtre deKalman linéaire qui estime les paramètres de la droite support des segments etles variances associées. Les algorithmes sont rapides et robustes au bruit etaux variations d'illumination de la scène perçue, ils permettent de détecterdes segments plus longs que les approches existantes guidées par les données(``data-driven''), et ils ne nécessitent pas de délicate détermination deparamètres. Des résultats avec différentes conditions d'éclairage et descomparaisons avec les approches existantes sont présentés.

[375] Anh Linh Nguyen and Andrzej Szalas. 2010.
Three-Valued Paraconsistent Reasoning for Semantic Web Agents.
In Proceedings of the 4th International KES Symposium on Agents and Multi-agent Systems ? Technologies and Applications (KES-AMSTA), pages 152–162. In series: Lecture Notes in Artificial Intelligence #6070. Springer. ISBN: 978-3-642-13479-1.
DOI: 10.1007/978-3-642-13480-7_17.

Description logics [1] refer to a family of formalisms concentrated around concepts, roles and individuals. They are used in many multiagent and semantic web applications as a foundation for specifying knowledge bases and reasoning about them. One of widely applied description logics is <em>SHIQ</em><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char53.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char48.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char49.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char51.png\" /> [7,8]. In the current paper we address the problem of inconsistent knowledge. Inconsistencies may naturally appear in the considered application domains, for example as a result of fusing knowledge from distributed sources. We define three three-valued paraconsistent semantics for <em>SHIQ</em><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char53.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char48.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char49.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char51.png\" />, reflecting different meanings of concept inclusion of practical importance. We also provide a quite general syntactic condition of safeness guaranteeing satisfiability of a knowledge base w.r.t. three-valued semantics and define a faithful translation of our formalism into a suitable version of a two-valued description logic. Such a translation allows one to use existing tools and <em>SHIQ</em><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char53.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char48.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char49.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char51.png\" /> reasoners to deal with inconsistent knowledge.

[374] Anh Linh Nguyen and Andrzej Szalas. 2010.
Tableaux with Global Caching for Checking Satisfiability of a Knowledge Base in the Description Logic SH.
Transactions on Computational Collective Intelligence, 1(1):21–38. Springer. ISBN: 978-3-642-15033-3.
DOI: 10.1007/978-3-642-15034-0_2.

Description logics (DLs) are a family of knowledge representation languages which can be used to represent the terminological knowledge of an application domain in a structured and formally well-understood way. DLs can be used, for example, for conceptual modeling or as ontology languages. In fact, OWL (Web Ontology Language), recommended by W3C, is based on description logics. In the current paper we give the first direct ExpTime (optimal) tableau decision procedure, which is not based on transformation or on the pre-completion technique, for checking satisfiability of a knowledge base in the description logic <em>SH</em><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char53.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char48.png\" />. Our procedure uses sound global caching and can be implemented as an extension of the highly optimized tableau prover TGC to obtain an efficient program for the mentioned satisfiability problem.

[373] Full text  Erik Sandewall. 2010.
Defeasible inheritance with doubt index and its axiomatic characterization.
Artificial Intelligence, 174(18):1431–1459. Elsevier.
DOI: 10.1016/j.artint.2010.09.001.

This article introduces and uses a representation of defeasible inheritance networks where links in the network are viewed as propositions, and where defeasible links are tagged with a quantitative indication of the proportion of exceptions, called the doubt index. This doubt index is used for restricting the length of the chains of inference. The representation also introduces the use of defeater literals that disable the chaining of subsumption links. The use of defeater literals replaces the use of negative defeasible inheritance links, expressing \"most A are not B\". The new representation improves the expressivity significantly. Inference in inheritance networks is defined by a combination of axioms that constrain the contents of network extensions, a heuristic restriction that also has that effect, and a nonmonotonic operation of minimizing the set of defeater literals while retaining consistency. We introduce an underlying semantics that defines the meaning of literals in a network, and prove that the axioms are sound with respect to this semantics. We also discuss the conditions for obtaining completeness. Traditional concepts, assumptions and issues in research on nonmonotonic or defeasible inheritance are reviewed in the perspective of this approach.

[372] Linh Anh Nguyen and Andrzej Szalas. 2010.
Checking Consistency of an ABox w.r.t. Global Assumptions in PDL.
Fundamenta Informaticae, 102(1):97–113. IOS Press.
DOI: 10.3233/FI-2010-299.

We reformulate Pratts tableau decision procedure of checking satisfiability of a set of formulas in PDL. Our formulation is simpler and its implementation is more direct. Extending the method we give the first Ex PT m E (optimal) tableau decision procedure not based on transformation for checking consistency of an ABox w.r.t. a TBox in PDL (here, PDL is treated as a description logic). We also prove a new result that the data complexity of the instance checking problem in PDL is coNP-complete.

[371] Full text  Patrick Doherty, Jonas KvarnstrŲm, Fredrik Heintz, David Landťn and Per-Magnus Olsson. 2010.
Research with Collaborative Unmanned Aircraft Systems.
In Gerhard Lakemeyer, Hector J. Levesque, Fiora Pirri, editors, Proceedings of the Dagstuhl Workshop on Cognitive Robotics. In series: Dagstuhl Seminar Proceedings #10081. Leibniz-Zentrum fŁr Informatik.

We provide an overview of ongoing research which targets development of a principled framework for mixed-initiative interaction with unmanned aircraft systems (UAS). UASs are now becoming technologically mature enough to be integrated into civil society. Principled interaction between UASs and human resources is an essential component in their future uses in complex emergency services or bluelight scenarios. In our current research, we have targeted a triad of fundamental, interdependent conceptual issues: delegation, mixed- initiative interaction and adjustable autonomy, that is being used as a basis for developing a principled and well-defined framework for interaction. This can be used to clarify, validate and verify different types of interaction between human operators and UAS systems both theoretically and practically in UAS experimentation with our deployed platforms.

[370] Full text  Oleg Burdakov, Patrick Doherty, Kaj Holmberg and Per-Magnus Olsson. 2010.
Optimal placement of UV-based communications relay nodes.
Journal of Global Optimization, 48(4):511–531. Springer.
DOI: 10.1007/s10898-010-9526-8.
Note: The original publication is available at www.springerlink.com:Oleg Burdakov, Patrick Doherty, Kaj Holmberg and Per-Magnus Olsson, Optimal placement of UV-based communications relay nodes, 2010, Journal of Global Optimization, (48), 4, 511-531.http://dx.doi.org/10.1007/s10898-010-9526-8Copyright: Springer Science Business Mediahttp://www.springerlink.com/
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

We consider a constrained optimization problem with mixed integer and real variables. It models optimal placement of communications relay nodes in the presence of obstacles. This problem is widely encountered, for instance, in robotics, where it is required to survey some target located in one point and convey the gathered information back to a base station located in another point. One or more unmanned aerial or ground vehicles (UAVs or UGVs) can be used for this purpose as communications relays. The decision variables are the number of unmanned vehicles (UVs) and the UV positions. The objective function is assumed to access the placement quality. We suggest one instance of such a function which is more suitable for accessing UAV placement. The constraints are determined by, firstly, a free line of sight requirement for every consecutive pair in the chain and, secondly, a limited communication range. Because of these requirements, our constrained optimization problem is a difficult multi-extremal problem for any fixed number of UVs. Moreover, the feasible set of real variables is typically disjoint. We present an approach that allows us to efficiently find a practically acceptable approximation to a global minimum in the problem of optimal placement of communications relay nodes. It is based on a spatial discretization with a subsequent reduction to a shortest path problem. The case of a restricted number of available UVs is also considered here. We introduce two label correcting algorithms which are able to take advantage of using some peculiarities of the resulting restricted shortest path problem. The algorithms produce a Pareto solution to the two-objective problem of minimizing the path cost and the number of hops. We justify their correctness. The presented results of numerical 3D experiments show that our algorithms are superior to the conventional Bellman-Ford algorithm tailored to solving this problem.

[369] Full text  Piotr Rudol, Mariusz Wzorek and Patrick Doherty. 2010.
Vision-based Pose Estimation for Autonomous Indoor Navigation of Micro-scale Unmanned Aircraft Systems.
In Proceedings of the 2010 IEEE†International Conference on Robotics and Automation (ICRA), pages 1913–1920. In series: Proceedings - IEEE International Conference on Robotics and Automation #2010. IEEE conference proceedings. ISBN: 978-1-4244-5038-1.
DOI: 10.1109/ROBOT.2010.5509203.

We present a navigation system for autonomous indoor flight of micro-scale Unmanned Aircraft Systems (UAS) which is based on a method for accurate monocular vision pose estimation. The method makes use of low cost artificial landmarks placed in the environment and allows for fully autonomous flight with all computation done on-board a UAS on COTS hardware. We provide a detailed description of all system components along with an accuracy evaluation and a time profiling result for the pose estimation method. Additionally, we show how the system is integrated with an existing micro-scale UAS and provide results of experimental autonomous flight tests. To our knowledge, this system is one of the first to allow for complete closed-loop control and goal-driven navigation of a micro-scale UAS in an indoor setting without requiring connection to any external entities.

[368] Full text  Mariusz Wzorek, Jonas KvarnstrŲm and Patrick Doherty. 2010.
Choosing Path Replanning Strategies for Unmanned Aircraft Systems.
In Ronen Brafman, H√©ctor Geffner, J√∂rg Hoffmann, Henry Kautz, editors, Proceedings of the Twentieth International Conference on Automated Planning and Scheduling (ICAPS), pages 193–200. AAAI Press. ISBN: 978-1-57735-449-9.

Unmanned aircraft systems use a variety of techniques to plan collision-free flight paths given a map of obstacles and no- fly zones. However, maps are not perfect and obstacles may change over time or be detected during flight, which may in- validate paths that the aircraft is already following. Thus, dynamic in-flight replanning is required.Numerous strategies can be used for replanning, where the time requirements and the plan quality associated with each strategy depend on the environment around the original flight path. In this paper, we investigate the use of machine learn- ing techniques, in particular support vector machines, to choose the best possible replanning strategy depending on the amount of time available. The system has been implemented, integrated and tested in hardware-in-the-loop simulation with a Yamaha RMAX helicopter platform.

[367] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2010.
Stream-Based Reasoning in DyKnow.
In Gerhard Lakemeyer and Hector J. Levesque and Fiora Pirri, editors, Proceedings of the Dagstuhl Workshop on Cognitive Robotics. In series: Dagstuhl Seminar Proceedings #10081. Leibniz-Zentrum fŁr Informatik.

The information available to modern autonomous systems is often in the form of streams. As the number of sensors and other stream sources increases there is a growing need for incremental reasoning about the incomplete content of sets of streams in order to draw relevant conclusions and react to new situations as quickly as possible. To act rationally, autonomous agents often depend on high level reasoning components that require crisp, symbolic knowledge about the environment. Extensive processing at many levels of abstraction is required to generate such knowledge from noisy, incomplete and quantitative sensor data. We define knowledge processing middleware as a systematic approach to integrating and organizing such processing, and argue that connecting processing components with streams provides essential support for steady and timely flows of information. DyKnow is a concrete and implemented instantiation of such middleware, providing support for stream reasoning at several levels. First, the formal kpl language allows the specification of streams connecting knowledge processes and the required properties of such streams. Second, chronicle recognition incrementally detects complex events from streams of more primitive events. Third, complex metric temporal formulas can be incrementally evaluated over streams of states. DyKnow and the stream reasoning techniques are described and motivated in the context of a UAV traffic monitoring application.

[366] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2010.
Stream-Based Middleware Support for Embedded Reasoning.
In Proceedings of the AAAI Spring Symposium on Embedded Reasoning: Intelligence in Embedded Systems (ER). AAAI Press. ISBN: 978-157735458-1.

For autonomous systems such as unmanned aerial vehicles to successfully perform complex missions, a great deal of embedded reasoning is required at varying levels of abstraction. In order to make use of diverse reasoning modules in such systems, issues of integration such as sensor data flow and information flow between such modules has to be taken into account. The DyKnow framework is a tool with a formal basis that pragmatically deals with many of the architectural issues which arise in such systems. This includes a systematic stream-based method for handling the sense-reasoning gap, caused by the wide difference in abstraction levels between the noisy data generally available from sensors and the symbolic, semantically meaningful information required by many high-level reasoning modules. DyKnow has proven to be quite robust and widely applicable to different aspects of hybrid software architectures for robotics.In this paper, we describe the DyKnow framework and show how it is integrated and used in unmanned aerial vehicle systems developed in our group. In particular, we focus on issues pertaining to the sense-reasoning gap and the symbol grounding problem and the use of DyKnow as a means of generating semantic structures representing situational awareness for such systems. We also discuss the use of DyKnow in the context of automated planning, in particular execution monitoring.

[365] Full text  Mattias Krysander, Fredrik Heintz, Jacob Roll and Erik Frisk. 2010.
FlexDx: A Reconfigurable Diagnosis Framework.
Engineering applications of artificial intelligence, 23(8):1303–1313. Elsevier.
DOI: 10.1016/j.engappai.2010.01.004.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Detecting and isolating multiple faults is a computationally expensive task. It typically consists of computing a set of tests and then computing the diagnoses based on the test results. This paper describes FlexDx, a reconfigurable diagnosis framework which reduces the computational burden while retaining the isolation performance by only running a subset of all tests that is sufficient to find new conflicts. Tests in FlexDx are thresholded residuals used to indicate conflicts in the monitored system. Special attention is given to the issues introduced by a reconfigurable diagnosis framework. For example, tests are added and removed dynamically, tests are partially performed on historic data, and synchronous and asynchronous processing are combined. To handle these issues FlexDx has been implemented using DyKnow, a stream-based knowledge processing middleware framework. Concrete methods for each component in the FlexDx framework are presented. The complete approach is exemplified on a dynamic system which clearly illustrates the complexity of the problem and the computational gain of the proposed approach.

[364] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2010.
Stream-Based Reasoning Support for Autonomous Systems.
In Proceedings of the 19th European Conference on Artificial Intelligence (ECAI). In series: Frontiers in Artificial Intelligence and Applications #215. IOS Press. ISBN: 978-1-60750-605-8.
DOI: 10.3233/978-1-60750-606-5-183.

For autonomous systems such as unmanned aerial vehicles to successfully perform complex missions, a great deal of embedded reasoning is required at varying levels of abstraction. To support the integration and use of diverse reasoning modules we have developed DyKnow, a stream-based knowledge processing middleware framework. By using streams, DyKnow captures the incremental nature of sensor data and supports the continuous reasoning necessary to react to rapid changes in the environment. DyKnow has a formal basis and pragmatically deals with many of the architectural issues which arise in autonomous systems. This includes a systematic stream-based method for handling the sense-reasoning gap, caused by the wide difference in abstraction levels between the noisy data generally available from sensors and the symbolic, semantically meaningful information required by many highlevel reasoning modules. As concrete examples, stream-based support for anchoring and planning are presented.

[363] Full text  Fredrik Heintz and Patrick Doherty. 2010.
Federated DyKnow, a Distributed Information Fusion System for Collaborative UAVs.
In Proceedings of the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV), pages 1063–1069. IEEE conference proceedings. ISBN: 978-1-4244-7814-9.
DOI: 10.1109/ICARCV.2010.5707967.

As unmanned aerial vehicle (UAV) applications are becoming more complex and covering larger physical areas there is an increasing need for multiple UAVs to cooperatively solve problems. To produce more complete and accurate information about the environment we present the DyKnow Federation framework for distributed fusion among collaborative UAVs. A federation is created and maintained using a multi-agent delegation framework which allows high-level specification and reasoning about resource bounded cooperative problem solving. When the federation is set up, local information is transparently shared between the agents according to specification. The work is presented in the context of a multi-UAV traffic monitoring scenario.

[362] Full text  Jonas KvarnstrŲm and Patrick Doherty. 2010.
Automated Planning for Collaborative UAV Systems.
In Proceedings of the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV), pages 1078–1085. IEEE conference proceedings. ISBN: 978-1-4244-7813-2, 978-1-4244-7814-9.
DOI: 10.1109/ICARCV.2010.5707969.
IEEE Explore: http://ieeexplore.ieee.org/xpls/abs_all....

Mission planning for collaborative Unmanned Aircraft Systems (UAS:s) is a complex topic which involves trade-offs between the degree of centralization or decentralization required, the degree of abstraction in which plans are generated, and the degree to which such plans are distributed among participating UAS:s. In realistic environments such as those found in naturaland man-made catastrophes where emergency services personnelare involved, a certain degree of centralization and abstractionis necessary in order for those in charge to understand andeventually sign off on potential plans. It is also quite often thecase that unconstrained distribution of actions is inconsistentwith the loosely coupled interactions and dependencies whicharise between collaborating systems. In this article, we presenta new planning algorithm for collaborative UAS:s based oncombining ideas from forward chaining planning with partialorderplanning leading to a new hybrid partial order forwardchaining(POFC) framework which meets the requirements oncentralization, abstraction and distribution we find in realisticemergency services settings.

[361] Full text  Per-Magnus Olsson, Jonas KvarnstrŲm, Patrick Doherty, Oleg Burdakov and Kaj Holmberg. 2010.
Generating UAV Communication Networks for Monitoring and Surveillance.
In Proceedings of the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010), pages 1070–1077. IEEE conference proceedings. ISBN: 978-1-4244-7814-9.
DOI: 10.1109/ICARCV.2010.5707968.

An important use of unmanned aerial vehicles is surveillance of distant targets, where sensor information must quickly be transmitted back to a base station. In many cases, high uninterrupted bandwidth requires line-of-sight between sender and transmitter to minimize quality degradation. Communication range is typically limited, especially when smaller UAVs are used. Both problems can be solved by creating relay chains for surveillance of a single target, and relay trees for simultaneous surveillance of multiple targets. In this paper, we show how such chains and trees can be calculated. For relay chains we create a set of chains offering different trade-offs between the number of UAVs in the chain and the chain’s cost. We also show new results on how relay trees can be quickly calculated and then incrementally improved if necessary. Encouraging empirical results for improvement of relay trees are presented.

[360] Full text  HŚkan Warnquist, Jonas KvarnstrŲm and Patrick Doherty. 2010.
Iterative Bounding LAO*.
In Helder Coelho, Rudi Studer and Mike Wooldridge, editors, ECAI 2010: 19th European Conference on Artificial Intelligence - Volume 215 Frontiers in Artificial Intelligence and Applications, pages 341–346. In series: Frontiers in Artificial Intelligence and Applications #215. IOS Press. ISBN: 978-1-60750-605-8, 978-1-60750-606-5.
DOI: 10.3233/978-1-60750-606-5-341.

Iterative Bounding LAO* is a new algorithm for epsilon- optimal probabilistic planning problems where an absorbing goal state should be reached at a minimum expected cost from a given initial state. The algorithm is based on the LAO* algorithm for finding optimal solutions in cyclic AND/OR graphs. The new algorithm uses two heuristics, one upper bound and one lower bound of the optimal cost. The search is guided by the lower bound as in LAO*, while the upper bound is used to prune search branches. The algorithm has a new mechanism for expanding search nodes, and while maintaining the error bounds, it may use weighted heuristics to reduce the size of the explored search space. In empirical tests on benchmark problems, Iterative Bounding LAO* expands fewer search nodes compared to state of the art RTDP variants that also use two-sided bounds.

[359] Full text  Jonas KvarnstrŲm. 2010.
Planning for Loosely Coupled Agents using Partial Order Forward-Chaining.
In Roland Bol, editor, The Swedish AI Society Workshop 2010, SAIS 2010, pages 45–54. In series: LinkŲping Electronic Conference Proceedings #48. LinkŲping University Electronic Press, LinkŲpings universitet.
Fulltext: http://www.ep.liu.se/ecp/048/009/ecp1048...

Partially ordered plan structures are highly suitable for centralized multi-agent planning, where plans should be minimally constrained in terms of precedence between actions performed by different agents. In many cases, however, any given agent will perform its own actions in strict sequence. We take advantage of this fact to develop a hybrid of temporal partial order planning and forward-chaining planning. A sequence of actions is constructed for each agent and linked to other agents' actions by a partially ordered precedence relation as required. When agents are not too tightly coupled, this structure enables the generation of partial but strong information about the state at the end of each agent's action sequence. Such state information can be effectively exploited during search. A prototype planner within this framework has been implemented, using precondition control formulas to guide the search process.

[358] Patrick Doherty and Andrzej Szalas. 2010.
On the Correctness of Rough-Set Based Approximate Reasoning.
In M. Szczuka, M. Kryszkiewicz, S. Ramanna, R. Jensen, Q. Hu, editors, Proceedings of the 7th International Conference on Rough Sets and Current Trends in Computing (RSCTC), pages 327–336. In series: Lecture Notes in Computer Science #6086. Springer. ISBN: 978-3-642-13528-6.
DOI: 10.1007/978-3-642-13529-3_35.

There is a natural generalization of an indiscernibility relation used in rough set theory, where rather than partitioning the universe of discourse into indiscernibility classes, one can consider a covering of the universe by similarity-based neighborhoods with lower and upper approximations of relations defined via the neighborhoods. When taking this step, there is a need to tune approximate reasoning to the desired accuracy. We provide a framework for analyzing self-adaptive knowledge structures. We focus on studying the interaction between inputs and output concepts in approximate reasoning. The problems we address are: -given similarity relations modeling approximate concepts, what are similarity relations for the output concepts that guarantee correctness of reasoning? -assuming that output similarity relations lead to concepts which are not accurate enough, how can one tune input similarities?

[357] Barbara Dunin-Keplicz, Linh Anh Nguyen and Andrzej Szalas. 2010.
A Framework for Graded Beliefs, Goals and Intentions.
Fundamenta Informaticae, 100(1-4):53–76. IOS Press.
DOI: 10.3233/FI-2010-263.

In natural language we often use graded concepts, reflecting different intensity degrees of certain features. Whenever such concepts appear in a given real-life context, they need to be appropriately expressed in its models. In this paper, we provide a framework which allows for extending the BGI model of agency by grading beliefs, goals and intentions. We concentrate on TEAMLOG [6, 7, 8, 9, 12] and provide a complexity-optimal decision method for its graded version TEAMLOG(K) by translating it into CPDLreg (propositional dynamic logic with converse and \"inclusion axioms\" characterized by regular languages). We also develop a tableau calculus which leads to the first EXPTIME (optimal) tableau decision procedure for CPDLreg. As CPDLreg is suitable for expressing complex properties of graded operators, the procedure can also be used as a decision tool for other multiagent formalisms.

[356] Barbara Dunin-Keplicz, Linh Anh Nguyen and Andrzej Szalas. 2010.
A Layered Rule-Based Architecture for Approximate Knowledge Fusion.
COMPUTER SCIENCE AND INFORMATION SYSTEMS, 7(3):617–642. COMSIS CONSORTIUM.
DOI: 10.2298/CSIS100209015D.

In this paper we present a framework for fusing approximate knowledge obtained from various distributed, heterogenous knowledge sources. This issue is substantial in modeling multi-agent systems, where a group of loosely coupled heterogeneous agents cooperate in achieving a common goal. In paper [5] we have focused on defining general mechanism for knowledge fusion. Next, the techniques ensuring tractability of fusing knowledge expressed as a Horn subset of propositional dynamic logic were developed in [13,16]. Propositional logics may seem too weak to be useful in real-world applications. On the other hand, propositional languages may be viewed as sublanguages of first-order logics which serve as a natural tool to define concepts in the spirit of description logics [2]. These notions may be further used to define various ontologies, like e. g. those applicable in the Semantic Web. Taking this step, we propose a framework, in which our Horn subset of dynamic logic is combined with deductive database technology. This synthesis is formally implemented in the framework of HSPDL architecture. The resulting knowledge fusion rules are naturally applicable to real-world data.

[355] Full text  Oleg Burdakov, Patrick Doherty, Kaj Holmberg, Jonas KvarnstrŲm and Per-Magnus Olsson. 2010.
Relay Positioning for Unmanned Aerial Vehicle Surveillance.
The international journal of robotics research, 29(8):1069–1087. Sage Publications.
DOI: 10.1177/0278364910369463.

When unmanned aerial vehicles (UAVs) are used for surveillance, information must often be transmitted to a base station in real time. However, limited communication ranges and the common requirement of free line of sight may make direct transmissions from distant targets impossible. This problem can be solved using relay chains consisting of one or more intermediate relay UAVs. This leads to the problem of positioning such relays given known obstacles, while taking into account a possibly mission-specific quality measure. The maximum quality of a chain may depend strongly on the number of UAVs allocated. Therefore, it is desirable to either generate a chain of maximum quality given the available UAVs or allow a choice from a spectrum of Pareto-optimal chains corresponding to different trade-offs between the number of UAVs used and the resulting quality. In this article, we define several problem variations in a continuous three-dimensional setting. We show how sets of Pareto-optimal chains can be generated using graph search and present a new label-correcting algorithm generating such chains significantly more efficiently than the best-known algorithms in the literature. Finally, we present a new dual ascent algorithm with better performance for certain tasks and situations.

[354] Barbara Dunin-Keplicz, Linh Anh Nguyen and Andrzej Szalas. 2010.
Tractable approximate knowledge fusion using the Horn fragment of serial propositional dynamic logic.
International Journal of Approximate Reasoning, 51(3):346–362. Elsevier.
DOI: 10.1016/j.ijar.2009.11.002.

In this paper we investigate a technique for fusing approximate knowledge obtained from distributed, heterogeneous information sources. This issue is substantial, e.g., in modeling multiagent systems, where a group of loosely coupled heterogeneous agents cooperate in achieving a common goal. Information exchange, leading ultimately to knowledge fusion, is a natural and vital ingredient of this process. We use a generalization of rough sets and relations [30], which depends on allowing arbitrary similarity relations. The starting point of this research is [6], where a framework for knowledge fusion in multiagent systems is introduced. Agents individual perceptual capabilities are represented by similarity relations, further aggregated to express joint capabilities of teams, This aggregation, expressing a shift from individual to social level of agents activity, has been formalized by means of dynamic logic. The approach of Doherty et al. (2007) [6] uses the full propositional dynamic logic, which does not guarantee tractability of reasoning. Our idea is to adapt the techniques of Nguyen [26-28] to provide an engine for tractable approximate database querying restricted to a Horn fragment of serial dynamic logic. We also show that the obtained formalism is quite powerful in applications.

[353] Karolina Eliasson. 2010.
A case-based approach to dialogue systems.
Journal of experimental and theoretical artificial intelligence (Print), 22(1):23–51. Taylor & Francis.
DOI: 10.1080/09528130902723708.

We describe an approach to integrate dialogue management, machine-learning and action planning in a system for dialogue between a human and a robot. Case-based techniques are used because they permit life-long learning from experience and demand little prior knowledge and few static hand-written structures. This approach has been developed through the work on an experimental dialogue system, called CEDERIC, that is connected to an unmanned aerial vehicle (UAV). A single case base and case-based reasoning engine is used both for understanding and for planning actions by the UAV. Dialogue experiments both with experienced and novice users, where the users have solved tasks by dialogue with this system, showed very adequate success rates.

[352] Full text  Fredrik Ňslin. 2010.
Evaluation of Hierarchical Temporal Memory in algorithmic trading.
Student Thesis. 32 pages. ISRN: LIU-IDA/LITH-EX-G--10/005--SE.

This thesis looks into how one could use Hierarchal Temporal Memory (HTM) networks to generate models that could be used as trading algorithms. The thesis begins with a brief introduction to algorithmic trading and commonly used concepts when developing trading algorithms. The thesis then proceeds to explain what an HTM is and how it works. To explore whether an HTM could be used to generate models that could be used as trading algorithms, the thesis conducts a series of experiments. The goal of the experiments is to iteratively optimize the settings for an HTM and try to generate a model that when used as a trading algorithm would have more profitable trades than losing trades. The setup of the experiments is to train an HTM to predict if it is a good time to buy some shares in a security and hold them for a fixed time before selling them again. A fair amount of the models generated during the experiments was profitable on data the model have never seen before, therefore the author concludes that it is possible to train an HTM so it can be used as a profitable trading algorithm.

[351] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2010.
Bridging the sense-reasoning gap: DyKnow - Stream-based middleware for knowledge processing.
Advanced Engineering Informatics, 24(1):14–26. Elsevier.
DOI: 10.1016/j.aei.2009.08.007.

Engineering autonomous agents that display rational and goal-directed behavior in dynamic physical environments requires a steady flow of information from sensors to high-level reasoning components. However, while sensors tend to generate noisy and incomplete quantitative data, reasoning often requires crisp symbolic knowledge. The gap between sensing and reasoning is quite wide, and cannot in general be bridged in a single step. Instead, this task requires a more general approach to integrating and organizing multiple forms of information and knowledge processing on different levels of abstraction in a structured and principled manner. We propose knowledge processing middleware as a systematic approach to organizing such processing. Desirable properties are presented and motivated. We argue that a declarative stream-based system is appropriate for the required functionality and present DyKnow, a concrete implemented instantiation of stream-based knowledge processing middleware with a formal semantics. Several types of knowledge processes are defined and motivated in the context of a UAV traffic monitoring application. In the implemented application, DyKnow is used to incrementally bridge the sense-reasoning gap and generate partial logical models of the environment over which metric temporal logical formulas are evaluated. Using such formulas, hypotheses are formed and validated about the type of vehicles being observed. DyKnow is also used to generate event streams representing for example changes in qualitative spatial relations, which are used to detect traffic violations expressed as declarative chronicles.

[350] Full text  Oleg Burdakov, Patrick Doherty, Kaj Holmberg, Jonas KvarnstrŲm and Per-Magnus Olsson. 2010.
Positioning Unmanned Aerial Vehicles As Communication Relays for Surveillance Tasks.
In J. Trinkle, Y. Matsuoka and J.A. Castellanos, editors, Robotics: Science and Systems V, pages 257–264. MIT Press. ISBN: 978-0-262-51463-7.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/12536749
Link to publication: http://www.roboticsproceedings.org/rss05...

When unmanned aerial vehicles (UAVs) are used to survey distant targets, it is important to transmit sensor information back to a base station. As this communication often requires high uninterrupted bandwidth, the surveying UAV often needs afree line-of-sight to the base station, which can be problematic in urban or mountainous areas. Communication ranges may also belimited, especially for smaller UAVs. Though both problems can be solved through the use of relay chains consisting of one or more intermediate relay UAVs, this leads to a new problem: Where should relays be placed for optimum performance? We present two new algorithms capable of generating such relay chains, one being a dual ascent algorithm and the other a modification of the Bellman-Ford algorithm. As the priorities between the numberof hops in the relay chain and the cost of the chain may vary, wecalculate chains of different lengths and costs and let the ground operator choose between them. Several different formulations for edge costs are presented. In our test cases, both algorithms are substantially faster than an optimized version of the original Bellman-Ford algorithm, which is used for comparison.

2009
[349] Mikael Nilsson. 2009.
SpannerŲar och spannervšgar.
Student Thesis. 126 pages. ISRN: -.

In this Master Thesis the possibility to efficiently divide a graph into spanner islands is examined. Spanner islands are islands of the graph that fulfill the spanner condition, that the distance between two nodes via the edges in the graph cannot be too far, regulated by the stretch constant, compared to the Euclidian distance between them. In the resulting division the least number of nodes connecting to other islands is sought-after. Different heuristics are evaluated with the conclusion that for dense graphs a heuristic using MAX-FLOW to divide problematic nodes gives the best result whereas for sparse graphs a heuristic using the single-link clustering method performs best. The problem of finding a spanner path, a path fulfilling the spanner condition, between two nodes is also investigated. The problem is proven to be NP-complete for a graph of size n if the spanner constant is greater than n^(1+1/k)*k^0.5 for some integer k. An algorithm with complexity O(2^(0.822n)) is given. A special type of graph where all the nodes are located on integer locations along the real line is investigated. An algorithm to solve this problem is presented with a complexity of O(2^((c*log n)^2))), where c is a constant depending only on the spanner constant. For instance, the complexity O(2^((5.32*log n)^2))) can be reached for stretch 1.5.

[348] Barbara Dunin-Keplicz, Linh Anh Nguyen and Andrzej Szalas. 2009.
Fusing Approximate Knowledge from Distributed Sources.
In Proceedings of the 3rd International Symposium on Intelligent Distributed Computing (IDC), pages 75–86. In series: Studies in Computational Intelligence #237. Springer Berlin/Heidelberg. ISBN: 978-3-642-03213-4, 978-3-642-26930-1.
DOI: 10.1007/978-3-642-03214-1_8.

In this paper we investigate a technique for fusing approximate knowledge obtained from distributed, heterogeneous information sources. We use a generalization of rough sets and relations [14], which depends on allowing arbitrary similarity relations. The starting point of this research is [2], where a framework for knowledge fusion in multi-agent systems is introduced. Agent’s individual perceptual capabilities are represented by similarity relations, further aggregated to express joint capabilities of teams. This aggregation, allowing a shift from individual to social level, has been formalized by means of dynamic logic. The approach of [2] uses the full propositional dynamic logic, not guaranteeing the tractability of reasoning. Therefore the results of [11, 12, 13] are adapted to provide a technical engine for tractable approximate database querying restricted to a Horn fragment of serial PDL. We also show that the obtained formalism is quite powerful in applications.

[347] Linh Anh Nguyen and Andrzej Szalas. 2009.
Checking Consistency of an ABox w.r.t. Global Assumptions in PDL*.
In Proceedings of the 18th Concurrency, Specification and Programming Workshop (CS&P), pages 431–442.

[346] Linh Anh Nguyen and Andrzej Szalas. 2009.
An Optimal Tableau Decision Procedure for Converse-PDL.
In Proceedings of the 1st International Conference on Knowlegde and Systems Engineering (KSE), pages 207–214. IEEE Computer Society. ISBN: 978-1-4244-5086-2.
DOI: 10.1109/KSE.2009.12.

We give a novel tableau calculus and an optimal (EXPTIME) tableau decision procedure based on the calculus for the satisfiability problem of propositional dynamic logic with converse. Our decision procedure is formulated with global caching and can be implemented together with useful optimization techniques.

[345] Cyrille Berger. 2009.
Perception de la gťomťtrie de l'environment pour la navigation autonome.
PhD Thesis. Universitť de Toulouse. 164 pages.

Le but de la recherche en robotique mobile est de donner aux robots la capacité d'accomplir des missions dans un environnement qui n'est pas parfaitement connu. Mission, qui consiste en l'exécution d'un certain nombre d'actions élémentaires (déplacement, manipulation d'objets...) et qui nécessite une localisation précise, ainsi que la construction d'un bon modèle géométrique de l'environnement, a partir de l'exploitation de ses propres capteurs, des capteurs externes, de l'information provenant d'autres robots et de modèle existant, par exemple d'un système d'information géographique. L'information commune est la géométrie de l'environnement. La première partie du manuscrit couvre les différentes méthodes d'extraction de l'information géométrique. La seconde partie présente la création d'un modèle géométrique en utilisant un graphe, ainsi qu'une méthode pour extraire de l'information du graphe et permettre au robot de se localiser dans l'environnement.

[344] Full text  Teresa Vidal-Calleja, Cyrille Berger, Joan Solŗ and Simon Lacroix. 2009.
Environment Modeling for Cooperative Aerial/Ground Robotic Systems.
In Proceedings of the 14th International Symposium on Robotics Research (ISRR), pages 681–696. In series: Springer Tracts in Advanced Robotics #70. Springer. ISBN: 978-3-642-19456-6.
DOI: 10.1007/978-3-642-19457-3_40.

This paper addresses the cooperative localization and visual mapping problem for multiple aerial and ground robots.We propose the use of heterogeneous visual landmarks, points and line segments. A large-scale SLAM algorithm is generalized to manage multiple robots, in which a global graph maintains the topological relationships between a series of local sub-maps built by the different robots. Only single camera setups are considered: in order to achieve undelayed initialization, we present a novel parametrization for lines based on anchored Pl√ľcker coordinates, to which we add extensible endpoints to enhance their representativeness. The built maps combine such lines with 3D points parametrized in inverse-depth. The overall approach is evaluated with real-data taken with a helicopter and a ground rover in an abandoned village.

[343] Full text  Teresa Vidal-Calleja, Cyrille Berger and Simon Lacroix. 2009.
Event-driven loop closure in multi-robot mapping.
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1535–1540. IEEE conference proceedings. ISBN: 978-1-4244-3803-7.
DOI: 10.1109/IROS.2009.5354335.

A large-scale mapping approach is combined with multiple robots events to achieve cooperative mapping. The mapping approach used is based on hierarchical SLAM -global level and local maps-, which is generalized for the multi-robot case. In particular, the consequences of multi-robot loop closing events (common landmarks detection and relative pose measurement between robots) are analyzed and managed at a global level. We present simulation results for each of these events using aerial and ground robots, and experimental results obtained with ground robots.

[342] Dov Gabbay and Andrzej Szalas. 2009.
Annotation Theories over Finite Graphs.
Studia Logica: An International Journal for Symbolic Logic, 93(2-3):147–180. Springer.
DOI: 10.1007/s11225-009-9220-3.

In the current paper we consider theories with vocabulary containing a number of binary and unary relation symbols. Binary relation symbols represent labeled edges of a graph and unary relations represent unique annotations of the graph’s nodes. Such theories, which we call <em>annotation theories</em>, can be used in many applications, including the formalization of argumentation, approximate reasoning, semantics of logic programs, graph coloring, etc. We address a number of problems related to annotation theories over finite models, including satisfiability, querying problem, specification of preferred models and model checking problem. We show that most of considered problems are NPTime- or co-NPTime-complete. In order to reduce the complexity for particular theories, we use second-order quantifier elimination. To our best knowledge none of existing methods works in the case of annotation theories. We then provide a new second-order quantifier elimination method for stratified theories, which is successful in the considered cases. The new result subsumes many other results, including those of [2, 28, 21].

[341] Full text  Anna PernestŚl, HŚkan Warnquist and Mattias Nyberg. 2009.
Modeling and Troubleshooting with Interventions Applied to an Auxiliary Truck Braking System.
In Proceedings of the 2nd IFAC Workshop on Dependable Control of Discrete Systems (DCDS), pages 251–256. ISBN: 978-390266144-9.
DOI: 10.3182/20090610-3-IT-4004.00048.

We consider computer assisted troubleshooting of complex systems, where the objective is to identify the cause of a failure and repair the system at as low expected cost as possible. Three main challenges are: the need for disassembling the system during troubleshooting, the difficulty to verify that the system is fault free, and the dependencies in between components and observations. We present a method that can return a response anytime, which allows us to obtain the best result given the available time. The work is based on a case study of an auxiliary braking system of a modern truck. We highlight practical issues related to model building and troubleshooting in a real environment.

[340] Aida Vitoria, Jan Maluszynski and Andrzej Szalas. 2009.
Modelling and Reasoning with Paraconsistent Rough Sets.
Fundamenta Informaticae, 97(4):405–438.
DOI: 10.3233/FI-2009-209.

We present a language for defining paraconsistent rough sets and reasoning about them. Our framework relates and brings together two major fields: rough sets [23] and paraconsistent logic programming [9]. To model inconsistent and incomplete information we use a four-valued logic. The language discussed in this paper is based on ideas of our previous work [21, 32, 22] developing a four-valued framework for rough sets. In this approach membership function, set containment and set operations are four-valued, where logical values are t (true), f (false), i (inconsistent) and u (unknown). We investigate properties of paraconsistent rough sets as well as develop a paraconsistent rule language, providing basic computational machinery for our approach.

[339] Anna PernestŚl, Mattias Nyberg and HŚkan Warnquist. 2009.
Modeling and Efficient Inference for Troubleshooting Automotive Systems.
Technical Report. In series: LiTH-ISY-R #2921. LinkŲpings universitet.

We consider computer assisted troubleshooting of automotive vehicles, where the objective is to repair the vehicle at as low expected cost as possible.The work has three main contributions: a troubleshooting method that applies to troubleshooting in real environments, the discussion on practical issues in modeling for troubleshooting, and the efficient probability computations.The work is based on a case study of an auxiliary braking system of a modern truck.We apply a decision theoretic approach, consisting of a planner and a diagnoser.Two main challenges in troubleshooting automotive vehicles are the need for disassembling the vehicle during troubleshooting to access parts to repair, and the difficulty to verify that the vehicle is fault free. These facts lead to that probabilities for faults and for future observations must be computed for a system that has been subject to external interventions that cause changes the dependency structure. The probability computations are further complicated due to the mixture of instantaneous and non-instantaneous dependencies.To compute the probabilities, we develop a method based on an algorithm, <em>updateBN</em>, that updates a static BN to account for the external interventions.

[338] Full text  HŚkan Warnquist, Jonas KvarnstrŲm and Patrick Doherty. 2009.
Planning as Heuristic Search for Incremental Fault Diagnosis and Repair.
In Proceedings of the Scheduling and Planning Applications Workshop (SPARK) at the 19th International Conference on Automated Planning and Scheduling (ICAPS).

In this paper we study the problem of incremental fault diagnosis and repair of mechatronic systems where the task is to choose actions such that the expected cost of repair is minimal. This is done by interleaving acting with the generation of partial conditional plans used to decide the next action. A diagnostic model based on Bayesian Networks is used to update the current belief state after each action. The planner uses a simplified version of this model to update predicted belief states. We have tested the approach in the domain of troubleshooting heavy vehicles. Experiments show that a simplified model for planning improves performance when troubleshooting with limited time.

[337] Full text  HŚkan Warnquist, Anna PernestŚl and Mattias Nyberg. 2009.
Anytime Near-Optimal Troubleshooting Applied to a Auxiliary Truck Braking System.
In Proceedings of the 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, pages 1306–1311. ISBN: 978-3-902661-46-3.
DOI: 10.3182/20090630-4-ES-2003.00212.

We consider computer assisted troubleshooting of complex systems, for example of a vehicle at a workshop. The objective is to identify the cause of a failure and repair a system at as low expected cost as possible. Three main challenges are: the need for disassembling the system during troubleshooting, the difficulty to verify that the system is fault free, and the dependencies in between components and observations. We present a method that can return a response anytime, which allows us to obtain the best result given the available time. The work is based on a case study of an auxiliary braking system of a modern truck. We highlight practical issues related to model building and troubleshooting in a real environment.

[336] Oleg Burdakov, Kaj Holmberg, Patrick Doherty and Per-Magnus Olsson. 2009.
Optimal placement of communications relay nodes.
Technical Report. In series: LiTH-MAT-R #2009:3. LinkŲpings universitet. 21 pages.

We consider a constrained optimization problem with mixed integer and real variables. It models optimal placement of communications relay nodes in the presence of obstacles. This problem is widely encountered, for instance, in robotics, where it is required to survey some target located in one point and convey the gathered information back to a base station located in another point. One or more unmanned aerial or ground vehicles (UAVs or UGVs) can be used for this purpose as communications relays. The decision variables are the number of unmanned vehicles (UVs) and the UV positions. The objective function is assumed to access the placement quality. We suggest one instance of such a function which is more suitable for accessing UAV placement. The constraints are determined by, firstly, a free line of sight requirement for every consecutive pair in the chain and, secondly, a limited communication range. Because of these requirements, our constrained optimization problem is a difficult multi-extremal problem for any fixed number of UVs. Moreover, the feasible set of real variables is typically disjoint. We present an approach that allows us to efficiently find a practically acceptable approximation to a global minimum in the problem of optimal placement of communications relay nodes. It is based on a spatial discretization with a subsequent reduction to a shortest path problem. The case of a restricted number of available UVs is also considered here. We introduce two label correcting algorithms which are able to take advantage of using some peculiarities of the resulting restricted shortest path problem. The algorithms produce a Pareto solution to the two-objective problem of minimizing the path cost and the number of hops. We justify their correctness. The presented results of numerical 3D experiments show that our algorithms are superior to the conventional Bellman-Ford algorithm tailored to solving this problem.

[335] Full text  Patrick Doherty and Jonas KvarnstrŲm. 2009.
Temporal Action Logics.
In V. Lifschitz, F. van Harmelen, and F. Porter, editors, Handbook of Knowledge Representation, pages 709–757. In series: Foundations of Artificial Intelligence #3. Elsevier. ISBN: 978-0-444-52211-5.
DOI: 10.1016/S1574-6526(07)03018-0.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/hitlist?d=libris&q=9...

The study of frameworks and formalisms for reasoning about action and change [67, 58, 61, 65, 70, 3, 57] has been central to the knowledge representation field almost from the inception of Artificial Intelligence as a general field of research [52, 56]. The phrase ‚ÄúTemporal Action Logics‚ÄĚ represents a class of logics for reasoning about action and change that evolved from Sandewall‚Äôs book on Features and Fluents [61] and owes much to this ambitious project. There are essentially three major parts to Sandewall‚Äôs work. He first developed a narrative-based logical framework for specifying agent behavior in terms of action scenarios. The logical framework is state-based and uses explicit time structures. He then developed a formal framework for assessing the correctness (soundness and completeness) of logics for reasoning about action and change relative to a set of well-defined intended conclusions, where reasoning problems were classified according to their ontological or epistemological characteristics. Finally, he proposed a number of logics defined semantically in terms of definitions of preferential entailment1 and assessed their correctness using his assessment framework.

[334] Full text  Martin Magnusson, David Landťn and Patrick Doherty. 2009.
Logical Agents that Plan, Execute, and Monitor Communication.
In Proceedings of the 2nd Workshop on Logic and the Simulation of Interaction and Reasoning (LSIR-2).

[333] Full text  Martin Magnusson and Patrick Doherty. 2009.
Planning Speech Acts in a Logic of Action and Change.
In Fredrik Heintz and Jonas Kvarnstr√∂m, editors, The Swedish AI Society Workshop 2009, SAIS 2009, pages 39–48. In series: LinkŲping Electronic Conference Proceedings #35. LinkŲping University Electronic Press, LinkŲpings universitet.
Fulltext: http://www.ep.liu.se/ecp/035/008/ecp0935...

Cooperation is a complex task that necessarily involves communication and reasoning about others’ intentions and beliefs. Multi-agent communication languages aid designers of cooperating robots through standardized speech acts, sometimes including a formal semantics. But a more direct approach would be to have the robots plan both regular and communicative actions themselves. We show how two robots with heterogeneous capabilities can autonomously decide to cooperate when faced with a task that would otherwise be impossible. Request and inform speech acts are formulated in the same first-order logic of action and change as is used for regular actions. This is made possible by treating the contents of communicative actions as quoted formulas of the same language. The robot agents then use a natural deduction theorem prover to generate cooperative plans for an example scenario by reasoning directly with the axioms of the theory.

[332] Full text  Patrick Doherty, Jonas KvarnstrŲm and Fredrik Heintz. 2009.
A Temporal Logic-based Planning and Execution Monitoring Framework for Unmanned Aircraft Systems.
Autonomous Agents and Multi-Agent Systems, 19(3):332–377. Springer.
DOI: 10.1007/s10458-009-9079-8.

Research with autonomous unmanned aircraft systems is reaching a new degree of sophistication where targeted missions require complex types of deliberative capability integrated in a practical manner in such systems. Due to these pragmatic constraints, integration is just as important as theoretical and applied work in developing the actual deliberative functionalities. In this article, we present a temporal logic-based task planning and execution monitoring framework and its integration into a fully deployed rotor-based unmanned aircraft system developed in our laboratory. We use a very challenging emergency services application involving body identification and supply delivery as a vehicle for showing the potential use of such a framework in real-world applications. TALplanner, a temporal logic-based task planner, is used to generate mission plans. Building further on the use of TAL (Temporal Action Logic), we show how knowledge gathered from the appropriate sensors during plan execution can be used to create state structures, incrementally building a partial logical model representing the actual development of the system and its environment over time. We then show how formulas in the same logic can be used to specify the desired behavior of the system and its environment and how violations of such formulas can be detected in a timely manner in an execution monitor subsystem. The pervasive use of logic throughout the higher level deliberative layers of the system architecture provides a solid shared declarative semantics that facilitates the transfer of knowledge between different modules.

[331] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2009.
Stream Reasoning in DyKnow: A Knowledge Processing Middleware System.
In Proceedings of the Stream Reasoning Workshop. In series: CEUR Workshop Proceedings #466. M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen.

The information available to modern autonomous systems is often in the form of streams. As the number of sensors and other stream sources increases there is a growing need for incremental reasoning about the incomplete content of sets of streams in order to draw relevant conclusions and react to new situations as quickly as possible. To act rationally, autonomous agents often depend on high level reasoning components that require crisp, symbolic knowledge about the environment. Extensive processing at many levels of abstraction is required to generate such knowledge from noisy, incomplete and quantitative sensor data. We define knowledge processing middleware as a systematic approach to integrating and organizing such processing, and argue that connecting processing components with streams provides essential support for steady and timely flows of information. DyKnow is a concrete and implemented instantiation of such middleware, providing support for stream reasoning at several levels. First, the formal KPL language allows the specification of streams connecting knowledge processes and the required properties of such streams. Second, chronicle recognition incrementally detects complex events from streams of more primitive events. Third, complex metric temporal formulas can be incrementally evaluated over streams of states. DyKnow and the stream reasoning techniques are described and motivated in the context of a UAV traffic monitoring application.

[330] Fredrik Heintz and Jonas KvarnstrŲm. 2009.
Proceedings of the Swedish AI Society Workshop 2009.
Conference Proceedings. In series: LinkŲping Electronic Conference Proceedings #35. LinkŲping University Electronic Press, LinkŲpings universitet. 65 pages.
Link to Book: http://www.ep.liu.se/ecp/035/

[329] Andrzej Szalas and Alicja Szalas. 2009.
Paraconsistent Reasoning with Words.
In Aspects of Natural Language Processing: Essays Dedicated to Leonard Bolc on the Occasion of His 75th Birthday, pages 43–58. In series: Lecture Notes in Computer Science #5070. Springer. ISBN: 978-3-642-04734-3.
DOI: 10.1007/978-3-642-04735-0_2.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/11741557

Fuzzy logics are one of the most frequent approaches to model uncertainty and vagueness. In the case of fuzzy modeling, degrees of belief and disbelief sum up to 1, which causes problems in modeling the lack of knowledge and inconsistency. Therefore, so called paraconsistent intuitionistic fuzzy sets have been introduced, where the degrees of belief and disbelief are not required to sum up to 1. The situation when this sum is smaller than 1 reflects the lack of knowledge and its value greater than 1 models inconsistency. In many applications there is a strong need to guide and interpret fuzzy-like reasoning using qualitative approaches. To achieve this goal in the presence of uncertainty, lack of knowledge and inconsistency, we provide a framework for qualitative interpretation of the results of fuzzy-like reasoning by labeling numbers with words, like <em>true, false, inconsistent, unknown</em>, reflecting truth values of a suitable, usually finitely valued logical formalism.

[328] Andrzej Szalas and Dov Gabbay. 2009.
Voting by Eliminating Quantifiers.
Studia Logica: An International Journal for Symbolic Logic, 92(3):365–379. Springer.
DOI: 10.1007/s11225-009-9200-7.

Mathematical theory of voting and social choice has attracted much attention. In the general setting one can view social choice as a method of aggregating individual, often conflicting preferences and making a choice that is the best compromise. How preferences are expressed and what is the ‚Äúbest compromise‚ÄĚ varies and heavily depends on a particular situation. The method we propose in this paper depends on expressing individual preferences of voters and specifying properties of the resulting ranking by means of first-order formulas. Then, as a technical tool, we use methods of second-order quantifier elimination to analyze and compute results of voting. We show how to specify voting, how to compute resulting rankings and how to verify voting protocols.

[327] Andrzej Szalas and Linh Anh Nguyen. 2009.
EXPTIME Tableaux for Checking Satisfiability of a Knowledge Base in the Description Logic ALC.
In Ngoc Thanh; Kowalczyk, Ryszard; Chen, Shyi-Ming, editors, Proceedings of the 1st International Conference on Computational Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems (ICCCI), pages 437–448. In series: Lecture Notes in Artificial Intelligence #5796. Springer. ISBN: 978-3-642-04440-3, 978-3-642-04441-0.
DOI: 10.1007/978-3-642-04441-0_38.

We give the first ExpTime (optimal) tableau decision procedure for checking satisfiability of a knowledge base in the description logic ALC, not based on transformation that encodes ABoxes by nominals or terminology axioms. Our procedure can be implemented as an extension of the highly optimized tableau prover TGC [12] to obtain an efficient program for the mentioned satisfiability problem.

[326] Full text  Martin Magnusson, Jonas KvarnstrŲm and Patrick Doherty. 2009.
Abductive Reasoning with Filtered Circumscription.
In Proceedings of the IJCAI-09 Workshop on Nonmonotonic Reasoning, Action and Change (NRAC). UTSePress. ISBN: 978-0-9802840-7-2.

For logical artificial intelligence to be truly useful,its methods must scale to problems of realistic size.An interruptible algorithm enables a logical agentto act in a timely manner to the best of its knowledge,given its reasoning so far. This seems necessaryto avoid analysis paralysis, trying to thinkof every potentiality, however unlikely, beforehand.These considerations prompt us to look for alternativereasoning mechanisms for filtered circumscription,a nonmonotonic reasoning formalism usede.g. by Temporal Action Logic and Event Calculus.We generalize Ginsberg’s circumscriptive theoremprover and describe an interruptible theoremprover based on abduction that has been used tounify planning and reasoning in a logical agent architecture.

[325] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2009.
A Stream-Based Hierarchical Anchoring Framework.
In Proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS). IEEE conference proceedings. ISBN: 978-1-4244-3803-7.
DOI: 10.1109/IROS.2009.5354372.
IEEE Xplore: http://ieeexplore.ieee.org/stamp/stamp.j...

[324] M. Wiggberg and Peter Dalenius. 2009.
Bridges and problem solving: Swedish engineering students' conceptions of engineering in 2007.
In Proceedings of the 1st International Conference on Computer Supported Education (CSEDU), pages 5–12. ISBN: 978-989-8111-82-1.

Swedish engineering students conceptions of engineering is investigated by a large nation-wide study in ten Swedish higher education institutions. Based on data from surveys and interviews, categories and top-lists, a picture of students conceptions of engineering is presented. Students conceptions of engineering, are somewhat divergent, but dealing with problems and their solutions and creativity are identified as core concepts. The survey data is in general more varied and deals with somewhat different kinds of terms. When explicitly asking for five engineering terms, as in the survey, a broader picture arises including terms, or concepts, denoting how students think of engineering and work in a more personal way. For example, words like hard work, stressful, challenging, interesting, and fun are used. On the other hand, it seems like the interviewed students tried to give more general answers that were not always connected to their personal experiences. Knowledge on students conceptions of engineering is essential for practitioners in engineering education. By information on students conceptions, the teaching can approach students at their particular mindset of the engineering field. Program managers with responsibility for design of engineering programs would also benefit using information on students conceptions of engineering. Courses could be motivated and contextualized in order to connect with the students. Recruitment officers would also have an easier time marketing why people should chose the engineering track.

[323] Linh Anh Nguyen and Andrzej Szalas. 2009.
A tableau calculus for regular grammar logics with converse.
In Proceedings of the 22nd International Conference on Automated Deduction (CADE), pages 421–436. In series: Lecture Notes in Artificial Intelligence #5663. Springer. ISBN: 978-364202958-5.
DOI: 10.1007/978-3-642-02959-2_31.

We give a sound and complete tableau calculus for deciding the general satisfiability problem of regular grammar logics with converse (REG c logics). Tableaux of our calculus are defined as \"and-or\" graphs with global caching. Our calculus extends the tableau calculus for regular grammar logics given by Goré and Nguyen [11] by using a cut rule and existential automaton-modal operators to deal with converse. We use it to develop an ExpTime (optimal) tableau decision procedure for the general satisfiability problem of REG c logics. We also briefly discuss optimizations for the procedure.

[322] Full text  Gianpaolo Conte and Patrick Doherty. 2009.
Vision-Based Unmanned Aerial Vehicle Navigation Using Geo-Referenced Information.
EURASIP Journal on Advances in Signal Processing, 2009(387308):1–18. Hindawi Publishing Corporation.
DOI: 10.1155/2009/387308.

This paper investigates the possibility of augmenting an Unmanned Aerial Vehicle (UAV) navigation system with a passive video camera in order to cope with long-term GPS outages. The paper proposes a vision-based navigation architecture which combines inertial sensors, visual odometry, and registration of the on-board video to a geo-referenced aerial image. The vision-aided navigation system developed is capable of providing high-rate and drift-free state estimation for UAV autonomous navigation without the GPS system. Due to the use of image-to-map registration for absolute position calculation, drift-free position performance depends on the structural characteristics of the terrain. Experimental evaluation of the approach based on offline flight data is provided. In addition the architecture proposed has been implemented on-board an experimental UAV helicopter platform and tested during vision-based autonomous flights.

[321] Full text  Gianpaolo Conte. 2009.
Vision-Based Localization and Guidance for Unmanned Aerial Vehicles.
PhD Thesis. In series: LinkŲping Studies in Science and Technology. Dissertations #1260. LinkŲping University Electronic Press. 174 pages. ISBN: 978-91-7393-603-3.
cover: http://liu.diva-portal.org/smash/get/div...

The thesis has been developed as part of the requirements for a PhD degree at the Artificial Intelligence and Integrated Computer System division (AIICS) in the Department of Computer and Information Sciences at Linköping University.The work focuses on issues related to Unmanned Aerial Vehicle (UAV) navigation, in particular in the areas of guidance and vision-based autonomous flight in situations of short and long term GPS outage.The thesis is divided into two parts. The first part presents a helicopter simulator and a path following control mode developed and implemented on an experimental helicopter platform. The second part presents an approach to the problem of vision-based state estimation for autonomous aerial platforms which makes use of geo-referenced images for localization purposes. The problem of vision-based landing is also addressed with emphasis on fusion between inertial sensors and video camera using an artificial landing pad as reference pattern. In the last chapter, a solution to a vision-based ground object geo-location problem using a fixed-wing micro aerial vehicle platform is presented.The helicopter guidance and vision-based navigation methods developed in the thesis have been implemented and tested in real flight-tests using a Yamaha Rmax helicopter. Extensive experimental flight-test results are presented.

[320] Full text  Tommy Persson. 2009.
Evaluating the use of DyKnow in multi-UAV traffic monitoring applications.
Student Thesis. 75 pages. ISRN: LIU-IDA/LITH-EX-A--09/019--SE.

This Master’s thesis describes an evaluation of the stream-based knowledge pro-cessing middleware framework DyKnow in multi-UAV traffic monitoring applica-tions performed at Saab Aerosystems. The purpose of DyKnow is “to providegeneric and well-structured software support for the processes involved in gen-erating state, object, and event abstractions about the environments of complexsystems.\" It does this by providing the concepts of streams, sources, computa-tional units (CUs), entity frames and chronicles.This evaluation is divided into three parts: A general quality evaluation ofDyKnow using the ISO 9126-1 quality model, a discussion of a series of questionsregarding the specific use and functionality of DyKnow and last, a performanceevaluation. To perform parts of this evaluation, a test application implementinga traffic monitoring scenario was developed using DyKnow and the Java AgentDEvelopment Framework (JADE).The quality evaluation shows that while DyKnow suffers on the usability side,the suitability, accuracy and interoperability were all given high marks.The results of the performance evaluation high-lights the factors that affect thememory and CPU requirements of DyKnow. It is shown that the most significantfactor in the demand placed on the CPU is the number of CUs and streams. Italso shows that DyKnow may suffer dataloss and severe slowdown if the CPU istoo heavily utilized. However, a reasonably sized DyKnow application, such as thescenario implemented in this report, should run without problems on systems atleast half as fast as the one used in the tests.

[319] Full text  Fredrik Heintz. 2009.
DyKnow: A Stream-Based Knowledge Processing Middleware Framework.
PhD Thesis. In series: LinkŲping Studies in Science and Technology. Dissertations #1240. LinkŲping University Electronic Press. 258 pages. ISBN: 9789173936965.
cover: http://liu.diva-portal.org/smash/get/div...

As robotic systems become more and more advanced the need to integrate existing deliberative functionalities such as chronicle recognition, motion planning, task planning, and execution monitoring increases. To integrate such functionalities into a coherent system it is necessary to reconcile the different formalisms used by the functionalities to represent information and knowledge about the world. To construct and integrate these representations and maintain a correlation between them and the environment it is necessary to extract information and knowledge from data collected by sensors. However, deliberative functionalities tend to assume symbolic and crisp knowledge about the current state of the world while the information extracted from sensors often is noisy and incomplete quantitative data on a much lower level of abstraction. There is a wide gap between the information about the world normally acquired through sensing and the information that is assumed to be available for reasoning about the world.As physical autonomous systems grow in scope and complexity, bridging the gap in an ad-hoc manner becomes impractical and inefficient. Instead a principled and systematic approach to closing the sensereasoning gap is needed. At the same time, a systematic solution has to be sufficiently flexible to accommodate a wide range of components with highly varying demands. We therefore introduce the concept of knowledge processing middleware for a principled and systematic software framework for bridging the gap between sensing and reasoning in a physical agent. A set of requirements that all such middleware should satisfy is also described.A stream-based knowledge processing middleware framework called DyKnow is then presented. Due to the need for incremental refinement of information at different levels of abstraction, computations and processes within the stream-based knowledge processing framework are modeled as active and sustained knowledge processes working on and producing streams. DyKnow supports the generation of partial and context dependent stream-based representations of past, current, and potential future states at many levels of abstraction in a timely manner.To show the versatility and utility of DyKnow two symbolic reasoning engines are integrated into Dy-Know. The first reasoning engine is a metric temporal logical progression engine. Its integration is made possible by extending DyKnow with a state generation mechanism to generate state sequences over which temporal logical formulas can be progressed. The second reasoning engine is a chronicle recognition engine for recognizing complex events such as traffic situations. The integration is facilitated by extending DyKnow with support for anchoring symbolic object identifiers to sensor data in order to collect information about physical objects using the available sensors. By integrating these reasoning engines into DyKnow, they can be used by any knowledge processing application. Each integration therefore extends the capability of DyKnow and increases its applicability.To show that DyKnow also has a potential for multi-agent knowledge processing, an extension is presented which allows agents to federate parts of their local DyKnow instances to share information and knowledge.Finally, it is shown how DyKnow provides support for the functionalities on the different levels in the JDL Data Fusion Model, which is the de facto standard functional model for fusion applications. The focus is not on individual fusion techniques, but rather on an infrastructure that permits the use of many different fusion techniques in a unified framework.The main conclusion of this thesis is that the DyKnow knowledge processing middleware framework provides appropriate support for bridging the sense-reasoning gap in a physical agent. This conclusion is drawn from the fact that DyKnow has successfully been used to integrate different reasoning engines into complex unmanned aerial vehicle (UAV) applications and that it satisfies all the stated requirements for knowledge processing middleware to a significant degree.

2008
[318] Gianpaolo Conte and Patrick Doherty. 2008.
Use of Geo-referenced Images with Unmanned Aerial Systems.
In Workshop Proceedings of SIMPAR 2008, International Conference on Simulation, Modeling and Programming for Autonomous Robots. Venice(Italy) 2008 November,3-4., pages 444–454. ISBN: 978-88-95872-01-8.

[317] Cyrille Berger and Simon Lacroix. 2008.
Modťlisation de l'environnement par facettes planes pour la Cartographie et la Localisation Simultanťes par stťrťovision.
In Reconnaissance des Formes et Intelligence Artificielle (RFIA).

[316] Full text  Cyrille Berger and Simon Lacroix. 2008.
Using planar facets for stereovision SLAM.
In Proceedings of the IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS), pages 1606–1611. IEEE conference proceedings. ISBN: 978-1-4244-2057-5.
DOI: 10.1109/IROS.2008.4650986.

In the context of stereovision SLAM, we propose a way to enrich the landmark models. Vision-based SLAM approaches usually rely on interest points associated to a point in the Cartesian space: by adjoining oriented planar patches (if they are present in the environment), we augment the landmark description with an oriented frame. Thanks to this additional information, the robot pose is fully observable with the perception of a single landmark, and the knowledge of the patches orientation helps the matching of landmarks. The paper depicts the chosen landmark model, the way to extract and match them, and presents some SLAM results obtained with such landmarks.

[315] Full text  Anders Holmberg and Per-Magnus Olsson. 2008.
Route Planning for Relay UAV.
In Proceedings of the 26th International Congress of the Aeronautical Sciences (ICAS). Optimage Ltd.. ISBN: ISBN 0-9533991-9-2.

<em>To expand the operative area for surveillance UAV, we propose the use of a relay UAV. The relay UAV is used as an intermediary node in a communication network: the surveillance UAV transmits data to the relay UAV, which sends it back to a ground station. In this exploratory report, we calculate the route for a relay UAV, to ensure communication at certain time points, given the route of the surveillance UAV. The results presented here are preliminary and may be considered </em><em>a first iteration of ideas and </em> <em>methods. </em>

[314] Full text  Joe Steinhauer. 2008.
Object Configuration Reconstruction from Descriptions using Relative and Intrinsic Reference Frames.
In ECAI 2008, pages 821–822. In series: Frontiers in Artificial Intelligence and Applications #178. IOS Press. ISBN: 978-1-58603-891-5.
DOI: 10.3233/978-1-58603-891-5-821.

We provide a technique to reconstruct an object configuration that has been described on site by only using intrinsic and relative frames of reference into an absolute frame of reference, as seen from the survey perspective.

[313] Full text  Per Nyblom and Patrick Doherty. 2008.
Towards Automatic Model Generation by Optimization.
In Proceedings of the Tenth Scandinavian Conference on Artificial Intelligence (SCAI), pages 114–123. In series: Frontiers in Artificial Intelligence and Applications #173. IOS Press. ISBN: 978-1-58603-867-0, e-978-1-60750-335-4.
Link to publication: http://www.booksonline.iospress.nl/Conte...

The problem of automatically selecting simulation models for autonomous agents depending on their current intentions and beliefs is considered in this paper. The intended use of the models is for prediction, filtering, planning and other types of reasoning that can be performed with Simulation models. The parameters and model fragments of the resulting model are selected by formulating and solving a hybrid constrained optimization problem that captures the intuition of the preferred model when relevance information about the elements of the world being modelled is taken into consideration. A specialized version of the original optimization problem is developed that makes it possible to solve the continuous subproblem analytically in linear time. A practical model selection problem is discussed where the aim is to select suitable parameters and models for tracking dynamic objects. Experiments with randomly generated problem instances indicate that a hillclimbing search approach might be both efficient and provides reasonably good solutions compared to simulated annealing and hillclimbing with random restarts.

[312] Full text  Rickard Karlsson, Thomas SchŲn, David TŲrnqvist, Gianpolo Conte and Fredrik Gustafsson. 2008.
Utilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application.
Technical Report. In series: LiTH-ISY-R #2836. LinkŲping University Electronic Press. 10 pages.

This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. Thesecond one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. Using the standard FastSLAM algorithm, only low-dimensional vehicle modelsare computationally feasible. In this work, an algorithm is introduced which merges FastSLAM and MPF, and the result is an algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a UAV (helicopter) are presented. The algorithmfuses measurements from on-board inertial sensors (accelerometer and gyro) and vision in order to solve the SLAM problem, i.e., enable navigation over a long period of time.

[311] Full text  HŚkan Warnquist and Mattias Nyberg. 2008.
A Heuristic for Near-Optimal Troubleshooting Using AO*.
In Proceedings of the International Workshop on the Principles of Diagnosis.

When troubleshooting malfunctioning technical equipment, the task is to locate faults and make repairsuntil the equipment functions properly again. The AO* algorithm can be used to find troubleshootingstrategies that are optimal in the sense that the expected cost of repair is minimal. We have adaptedthe AO* algorithm for troubleshooting in the automotive domain with limited time. We propose a newheuristic based on entropy. By using this heuristic, near-optimal strategies can be found within a fixedtime limit. This is shown in empirical studies on a fuel injection system of a truck. In these results, theAO* algorithm using the new heuristic, performs better than other troubleshooting algorithms.

[310] Full text  HŚkan Warnquist, Mattias Nyberg and Petter Sšby. 2008.
Troubleshooting when Action Costs are Dependent with Application to a Truck Engine.
In 10th Scandinavian Conference on Artificial Intelligence, SCAI 2008, pages 68–75. In series: Frontiers in Artificial Intelligence and Applications #173. IOS Press. ISBN: 978-1-58603-867-0, e-978-1-60750-335-4.
Link to paper: http://books.google.se/books?id=eju691VM...

We propose a troubleshooting algorithm that can troubleshoot systems with dependent action costs. When actions are performed they may change the way the system is decomposed and affect the cost of future actions. We present a way to model this by extending the traditional troubleshooting model with an additional state that describes which parts of the system that are decomposed. The proposed troubleshooting algorithm searches an AND/OR graph with the aim of finding the repair plan that minimizes the expected cost of repair. We present the heuristics needed to speed up the search and make it competitive with other troubleshooting algorithms. Finally, the performance of the algorithm is evaluated on a probabilistic model of a fuel injection system of a truck.We show that the expected cost of repair can be reduced when compared with an algorithm from previous literature.

[309] Full text  Erik Johan Sandewall. 2008.
Extending the concept of publication: Factbases and knowledgebases.
Learned Publishing, 21(2):123–131. Association of Learned and Professional Society Publishers.
DOI: 10.1087/095315108X288893.

The concept of a 'publication' no longer applies only to printed works, information technology has extended its application to several other types of works. This article describes a facility called the Common Knowledge Library that publishes modules of formally structured information representing facts and knowledge of various kinds. Publications of this new type have some characteristics in common with databases, and others in common with software modules, however, they also share some important characteristics with traditional publications. A framework for citation of previous work is important in order to provide an incentive for contributors of such modules. Peer review - the traditional method of quality assurance for scientific articles - must also be applied, although in a modified form, for fact and knowledge modules. The construction of the Common Knowledge Library is a cumulative process, new contributions are obtained by interpreting the contents of existing knowledge sources on the Internet, and the existing contents of the Library are an important resource for that interpretation process.

[308] Full text  Gianpaolo Conte and Patrick Doherty. 2008.
An Integrated UAV Navigation System Based on Aerial Image Matching.
In IEEE Aerospace Conference 2008,2008, pages 3142–3151. In series: IEEE Aerospace Conference #??. IEEE. ISBN: 978-1-4244-1487-1, 978-1-4244-1488-8.
DOI: 10.1109/AERO.2008.4526556.

The aim of this paper is to explore the possibility of using geo-referenced satellite or aerial images to augment an Unmanned Aerial Vehicle (UAV) navigation system in case of GPS failure. A vision based navigation system which combines inertial sensors, visual odometer and registration of a UAV on-board video to a given geo-referenced aerial image has been developed and tested on real flight-test data. The experimental results show that it is possible to extract useful position information from aerial imagery even when the UAV is flying at low altitude. It is shown that such information can be used in an automated way to compensate the drift of the UAV state estimation which occurs when only inertial sensors and visual odometer are used.

[307] Full text  Gianpaolo Conte, Maria Hempel, Piotr Rudol, David LundstrŲm, Simone Duranti, Mariusz Wzorek and Patrick Doherty. 2008.
High Accuracy Ground Target Geo-Location Using Autonomous Micro Aerial Vehicle Platforms.
In Proceedings of the AIAA Guidance, Navigation, and Control Conference (GNC). AIAA. ISBN: 978-1-56347-945-8.

This paper presents a method for high accuracy ground target localization using a Micro Aerial Vehicle (MAV) equipped with a video camera sensor. The proposed method is based on a satellite or aerial image registration technique. The target geo-location is calculated by registering the ground target image taken from an on-board video camera with a geo- referenced satellite image. This method does not require accurate knowledge of the aircraft position and attitude, therefore it is especially suitable for MAV platforms which do not have the capability to carry accurate sensors due to their limited payload weight and power resources. The paper presents results of a ground target geo-location experiment based on an image registration technique. The platform used is a MAV prototype which won the 3rd US-European Micro Aerial Vehicle Competition (MAV07). In the experiment a ground object was localized with an accuracy of 2.3 meters from a ight altitude of 70 meters.

[306] Full text  Piotr Rudol and Patrick Doherty. 2008.
Human Body Detection and Geolocalization for UAV Search and Rescue Missions Using Color and Thermal Imagery.
In Proceedings of the IEEE Aerospace Conference, pages 1–8. In series: Aerospace Conference Proceedings #2008. IEEE. ISBN: 978-1-4244-1488-8, 978-1-4244-1487-1.
DOI: 10.1109/AERO.2008.4526559.

Recent advances in the field of Unmanned Aerial Vehicles (UAVs) make flying robots suitable platforms for carrying sensors and computer systems capable of performing advanced tasks. This paper presents a technique which allows detecting humans at a high frame rate on standard hardware onboard an autonomous UAV in a real-world outdoor environment using thermal and color imagery. Detected human positions are geolocated and a map of points of interest is built. Such a saliency map can, for example, be used to plan medical supply delivery during a disaster relief effort. The technique has been implemented and tested on-board the UAVTech<sup>1</sup> autonomous unmanned helicopter platform as a part of a complete autonomous mission. The results of flight- tests are presented and performance and limitations of the technique are discussed.

[305] Andrzej Szalas. 2008.
Towards Incorporating Background Theories into Quantifier Elimination.
Journal of applied non-classical logics, 18(2-3):325–340. …ditions HermŤs-Lavoisier.
DOI: 10.3166/jancl.18.325-340.

In the paper we present a technique for eliminating quantifiers of arbitrary order, in particular of first-order. Such a uniform treatment of the elimination problem has been problematic up to now, since techniques for eliminating first-order quantifiers do not scale up to higher-order contexts and those for eliminating higher-order quantifiers are usually based on a form of monotonicity w.r.t implication (set inclusion) and are not applicable to the first-order case. We make a shift to arbitrary relations \"ordering\" the underlying universe. This allows us to incorporate background theories into higher-order quantifier elimination methods which, up to now, has not been achieved. The technique we propose subsumes many other results, including the Ackermann's lemma and various forms of fixpoint approaches when the \"ordering\" relations are interpreted as implication and reveals the common principle behind these approaches.

[304] Full text  Erik Sandewall. 2008.
Artificial Intelligence Needs Open-Access Knowledgebase Contents.
In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI), pages 1602–1605. AAAI Press. ISBN: 978-1-57735-368-3, 978-1-57735-367-6.
Note: Senior Members track

A substantial knowledgebase is an important part of many A.I. applications as well as (arguably) in any system that is claimed to implement broad-range intelligence. Although this has been an accepted view in our field since very long, little progress has been made towards the establishment of large and sharable knowledgebases. Both basic research projects and applications projects have found it necessary to construct special-purpose knowledgebases for their respective needs. This is obviously a problem: it would save work and speed up progress if the construction of a broadly sharable and broadly useful knowledgebase could be a joint undertaking for the field. In this article I wish to discuss the possibilities and the obstacles in this respect. I shall argue that the field of Knowledge Representation needs to adopt a new and very different paradigm in order for progress to be made, so that besides working as usual on logical foundations and on algorithms, we should also devote substantial efforts to the systematic preparation of knowledgebase contents.

[303] Patrick Doherty and Andrzej Szalas. 2008.
Reasoning with Qualitative Preferences and Cardinalities Using Generalized Circumscription.
In Gerhard Brewka, J√©r√īme Lang, editors, Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 560–570. AAAI Press. ISBN: 978-1-57735-384-3.

The topic of preference modeling has recently attracted the interest of a number of sub-disciplines in artificial intelligence such as the nonmonotonic reasoning and action and change communities. The approach in these communities focuses on qualitative preferences and preference models which provide more natural representations from a~commonsense perspective. In this paper, we show how generalized circumscription can be used as a highly expressive framework for qualitative preference modeling. Generalized circumscription proposed by Lifschitz allows for predicates (and thus formulas) to be minimized relative to arbitrary pre-orders (reflexive and transitive). Although it has received little attention, we show how it may be used to model and reason about elaborate qualitative preference relations. One of the perceived weaknesses with any type of circumscription is the 2nd-order nature of the representation. The paper shows how a large variety of preference theories represented using generalized circumscription can in fact be reduced to logically equivalent first-order theories in a constructive way. Finally, we also show how preference relations represented using general circumscription can be extended with cardinality constraints and when these extensions can also be reduced to logically equivalent first-order theories.

[302] Dov M. Gabbay, Renate A. Schmidt and Andrzej Szalas. 2008.
Second-Order Quantifier Elimination. Foundations, Computational Aspects and Applications.
Book. In series: Studies in Logics #12. College Publications. 308 pages. ISBN: 978-1-904987-56-7, 1-904-98-756-7.
link: http://www.amazon.com/Second-Order-Quant...

In recent years there has been an increasing use of logical methods and significant new developments have been spawned in several areas of computer science, ranging from artificial intelligence and software engineering to agent-based systems and the semantic web. In the investigation and application of logical methods there is a tension between: * the need for a representational language strong enough to express domain knowledge of a particular application, and the need for a logical formalism general enough to unify several reasoning facilities relevant to the application, on the one hand, and * the need to enable computationally feasible reasoning facilities, on the other hand. Second-order logics are very expressive and allow us to represent domain knowledge with ease, but there is a high price to pay for the expressiveness. Most second-order logics are incomplete and highly undecidable. It is the quantifiers which bind relation symbols that make second-order logics computationally unfriendly. It is therefore desirable to eliminate these second-order quantifiers, when this is mathematically possible; and often it is. If second-order quantifiers are eliminable we want to know under which conditions, we want to understand the principles and we want to develop methods for second-order quantifier elimination. This book provides the first comprehensive, systematic and uniform account of the state-of-the-art of second-order quantifier elimination in classical and non-classical logics. It covers the foundations, it discusses in detail existing second-order quantifier elimination methods, and it presents numerous examples of applications and non-standard uses in different areas. These include: * classical and non-classical logics, * correspondence and duality theory, * knowledge representation and description logics, * commonsense reasoning and approximate reasoning, * relational and deductive databases, and * complexity theory. The book is intended for anyone interested in the theory and application of logics in computer science and artificial intelligence.

[301] Full text  Erik Sandewall. 2008.
The Leordo Computation System.
In Yves Bertot, G√©rard Huet, Jean-Jacques L√©vy, Gordon Plotkin., editors, From Semantics to Computer Science: Essays in Honour of Gilles Kahn, pages 309–336. Cambridge University Press. ISBN: 978-05-21-51825-3, 978-05-11-77052-4.
DOI: 10.1017/CBO9780511770524.015.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/12013235
l√§s hela texten: http://ebooks.cambridge.org/ebook.jsf?bi...
link: http://www.amazon.com/From-Semantics-Com...

Gilles Kahn was one of the most influential figures in the development of computer science and information technology, not only in Europe but throughout the world. This volume of articles by several leading computer scientists serves as a fitting memorial to Kahn's achievements and reflects the broad range of subjects to which he contributed through his scientific research and his work at INRIA, the French National Institute for Research in Computer Science and Control. The editors also reflect upon the future of computing: how it will develop as a subject in itself and how it will affect other disciplines, from biology and medical informatics, to web and networks in general. Its breadth of coverage, topicality, originality and depth of contribution, make this book a stimulating read for all those interested in the future development of information technology.

[300] H.Joe Steinhauer. 2008.
Object Configuration Reconstruction from Incomplete Binary Object Relation Descriptions.
In Dengel, A.; Berns, K.; Breuel, Th.; Bomarius, F.; Roth-Berghofer, Th.R., editors, Proceedings of the 31st German Conference on Advances in Artificial Intelligence (KI), pages 348–355. In series: Lecture Notes in Computer Science #5243. Springer. ISBN: 978-3-540-85844-7.
DOI: 10.1007/978-3-540-85845-4_43.

We present a process for reconstructing object configurations described by a set of spatial constraints of the form (A northeast B) into a two-dimensional grid. The reconstruction process is cognitively easy for a person to fulfill and guides the user to avoid typical mistakes. For underspecified object configuration descriptions we suggest a strategy to handle coarse object relationships by representing a coarse object in a way that all disjunctive basic relationships that the coarse relationship consists of are represented within one reconstruction.

[299] Full text  Erik Sandewall. 2008.
A Review of the Handbook of Knowledge Representation.
Artificial Intelligence, 172(18):1965–1966. Elsevier.
DOI: 10.1016/j.artint.2008.10.002.

The newly appeared Handbook of Knowledge Representation is an impressive piece of work. Its three editors and its forty-five contributors have produced twenty-five concise, textbook-style chapters that introduce most of the major aspects of the science of knowledge representation. Reading this book is a very positive experience: it demonstrates the breadth, the depth and the coherence that our field has achieved by now.

[298] Full text  Fredrik Heintz and Patrick Doherty. 2008.
DyKnow Federations: Distributing and Merging Information Among UAVs.
In Proceedings of the 11th International Conference on Information Fusion (FUSION). IEEE conference proceedings. ISBN: 978-3-8007-3092-6.

As unmanned aerial vehicle (UAV) applications become more complex and versatile there is an increasing need to allow multiple UAVs to cooperate to solve problems which are beyond the capability of each individual UAV. To provide more complete and accurate information about the environment we present a DyKnow federation framework for information integration in multi-node networks of UAVs. A federation is created and maintained using a multiagent delegation framework and allows UAVs to share local information as well as process information from other UAVs as if it were local using the DyKnow knowledge processing middleware framework. The work is presented in the context of a multi UAV traffic monitoring scenario.

[297] Full text  Martin Magnusson and Patrick Doherty. 2008.
Temporal Action Logic for Question Answering in an Adventure Game.
In Artificial General Intelligence, AGI 2008, pages 236–247. In series: Frontiers in Artificial Intelligence and Applications #15. IOS Press. ISBN: 978-1-58603-833-5.

Inhabiting the complex and dynamic environments of modern computer games with autonomous agents capable of intelligent timely behaviour is a significant research challenge. We illustrate this using Our own attempts to build a practical agent architecture on it logicist foundation. In the ANDI-Land adventure game concept players solve puzzles by eliciting information from computer characters through natural language question answering. While numerous challenges immediately presented themselves, they took on a form of concrete and accessible problems to solve, and we present some of our initial solutions. We conclude that games, due to their demand for human-like computer characters with robust and independent operation in large simulated worlds, might serve as excellent test beds for research towards artificial general intelligence.

[296] Full text  Martin Magnusson, David Landťn and Patrick Doherty. 2008.
Planning, Executing, and Monitoring Communication in a Logic-Based Multi-Agent System.
In ECAI 2008, pages 933–934. In series: Frontiers in Artificial Intelligence and Applications #178. IOS Press. ISBN: 978-1-58603-891-5.
DOI: 10.3233/978-1-58603-891-5-933.

[295] Full text  Martin Magnusson and Patrick Doherty. 2008.
Deductive Planning with Inductive Loops.
In Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 528–534. AAAI Press. ISBN: 978-1-57735-384-3.

Agents plan to achieve and maintain goals. Maintenance that requires continuous action excludes the representation of plans as finite sequences of actions. If there is no upper bound on the number of actions, a simple list of actions would be infinitely long. Instead, a compact representation requires some form of looping construct. We look at a specific temporally extended maintenance goal, multiple target video surveillance, and formalize it in Temporal Action Logic. The logic's representation of time as the natural numbers suggests using mathematical induction to deductively plan to satisfy temporally extended goals. Such planning makes use of a sound and useful, but incomplete, induction rule that compactly represents the solution as a recursive fixpoint formula. Two heuristic rules overcome the problem of identifying a sufficiently strong induction hypothesis and enable an automated solution to the surveillance problem that satisfies the goal indefinitely.

[294] Full text  Martin Magnusson and Patrick Doherty. 2008.
Logical Agents for Language and Action.
In 4th International Artificial Intelligence and Interactive Digital Entertainment Conference AIIDE 2008,2008. AAAI Press. ISBN: 978-1-57735-391-1.

[293] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2008.
Bridging the Sense-Reasoning Gap: DyKnow - A Middleware Component for Knowledge Processing.
In Martin Hulse and Manfred Hild, editors, IROS Workshop on Current Software Frameworks in Cognitive Robotics Integrating Different Computational Paradigms.
Note: No proceedings, but CD

Developing autonomous agents displaying rational and goal-directed behavior in a dynamic physical environment requires the integration of both sensing and reasoning components. Due to the different characteristics of these components there is a gap between sensing and reasoning. We believe that this gap can not be bridged in a single step with a single technique. Instead, it requires a more general approach to integrating components on many different levels of abstraction and organizing them in a structured and principled manner. In this paper we propose knowledge processing middleware as a systematic approach for organizing such processing. Desirable properties of such middleware are presented and motivated. We then go on to argue that a declarative streambased system is appropriate to provide the desired functionality. Finally, DyKnow, a concrete example of stream-based knowledge processing middleware that can be used to bridge the sense-reasoning gap, is presented. Different types of knowledge processes and components of the middleware are described and motivated in the context of a UAV traffic monitoring application.

[292] Full text  Jonas KvarnstrŲm, Fredrik Heintz and Patrick Doherty. 2008.
A Temporal Logic-Based Planning and Execution Monitoring System.
In Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS). AAAI Press. ISBN: 978-1-57735-386-7, 978-1-57735-387-4.

As no plan can cover all possible contingencies, the ability to detect failures during plan execution is crucial to the robustness of any autonomous system operating in a dynamic and uncertain environment. In this paper we present a general planning and execution monitoring system where formulas in an expressive temporal logic specify the desired behavior of a system and its environment. A unified domain description for planning and monitoring provides a solid shared declarative semantics permitting the monitoring of both global and operator-specific conditions. During plan execution, an execution monitor subsystem detects violations of monitor formulas in a timely manner using a progression algorithm on incrementally generated partial logical models. The system has been integrated on a fully deployed autonomous unmanned aircraft system. Extensive empirical testing has been performed using a combination of actual flight tests and hardware-in-the-loop simulations in a number of different mission scenarios.

[291] Full text  Per-Magnus Olsson and Patrick Doherty. 2008.
The Observer Algorithm For Visibility Approximation.
In 10th Scandinavian Conference on Artificial Intelligence, SCAI 2008, pages 3–11. In series: Frontiers in Artificial Intelligence and Applications #173. IOS Press. ISBN: 978-1-58603-867-0, e-978-1-60750-335-4.
Link to paper: http://books.google.se/books?id=eju691VM...

We present a novel algorithm for visibility approximation that is substantially faster than ray casting based algorithms. The algorithm does not require extensive preprocessing or specialized hardware as most other algorithms do. We test this algorithm in several settings: rural, mountainous and urban areas, with different view ranges and grid cell sizes. By changing the size of the grid cells that the algorithm uses, it is possible to tailor the algorithm between speed and accuracy.

[290] Rickard Karlsson, Thomas SchŲn, David TŲrnqvist, Gianpaolo Conte and Fredrik Gustafsson. 2008.
Utilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application.
In Proceedings of the 2008 IEEE Aerospace Conference, pages 1–10. ISBN: 978-1-4244-1487-1, 978-1-4244-1488-8.
DOI: 10.1109/AERO.2008.4526442.
Related report: http://urn.kb.se/resolve?urn=urn:nbn:se:...

This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. The second one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. Using the standard FastSLAM algorithm, only low-dimensional vehicle models are computationally feasible. In this work, an algorithm is introduced which merges FastSLAM and MPF, and the result is an algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a UAV (helicopter) are presented. The algorithm fuses measurements from on-board inertial sensors (accelerometer and gyro) and vision in order to solve the SLAM problem, i.e., enable navigation over a long period of time.

[289] Full text  Mattias Krysander, Fredrik Heintz, Jacob Roll and Erik Frisk. 2008.
Dynamic Test Selection for Reconfigurable Diagnosis.
In Proceedings of the 47th IEEE Conference on Decision and Control, pages 1066–1072. In series: IEEE Conference on Decision and Control. Proceedings #??. IEEE. ISBN: 978-1-4244-3124-3, 978-1-4244-3123-6.
DOI: 10.1109/CDC.2008.4738793.

Detecting and isolating multiple faults is a computationally intense task which typically consists of computing a set of tests, and then computing the diagnoses based on the test results. This paper proposes a method to reduce the computational burden by only running the tests that are currently needed, and dynamically starting new tests when the need changes. A main contribution is a method to select tests such that the computational burden is reduced while maintaining the isolation performance of the diagnostic system. Key components in the approach are the test selection algorithm, the test initialization procedures, and a knowledge processing framework that supports the functionality needed. The approach is exemplified on a relatively small dynamical system, which still illustrates the complexity and possible computational gain with the proposed approach.

[288] Full text  Aida Vitoria, Andrzej Szalas and Jan Maluszynski. 2008.
Four-valued Extension of Rough Sets.
In Proceedings of the 3rd International Conference Rough Sets and Knowledge Technology (RSKT), pages 106–114. In series: Lecture Notes in Computer Science #5009. Springer. ISBN: 978-3-540-79720-3.
DOI: 10.1007/978-3-540-79721-0_19.

Rough set approximations of Pawlak [15] are sometimes generalized by using similarities between objects rather than elementary sets. In practical applications, both knowledge about properties of objects and knowledge of similarity between objects can be incomplete and inconsistent. The aim of this paper is to define set approximations when all sets, and their approximations, as well as similarity relations are four-valued. A set is four-valued in the sense that its membership function can have one of the four logical values: unknown (<strong>u</strong>), false (<strong>f</strong>), inconsistent (<strong>i</strong>), or true (<strong>t</strong>). To this end, a new implication operator and set-theoretical operations on four-valued sets, such as set containment, are introduced. Several properties of lower and upper approximations of four-valued sets are also presented.

[287] Jan Maluszynski, Aida Vitoria and Andrzej Szalas. 2008.
Paraconsistent Logic Programs with Four-valued Rough Sets.
In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pages 41–51. In series: Lecture Notes in Computer Science #5306. Springer. ISBN: 978-3-540-88423-1, 978-3-540-88425-5.
DOI: 10.1007/978-3-540-88425-5_5.

This paper presents a language for defining four-valued rough sets and to reason about them. Our framework brings together two major fields: rough sets and paraconsistent logic programming. On the one hand it provides a paraconsistent approach, based on four-valued rough sets, for integrating knowledge from different sources and reasoning in the presence of inconsistencies. On the other hand, it also caters for a specific type of uncertainty that originates from the fact that an agent may perceive different objects of the universe as being indiscernible. This paper extends the ideas presented in [9]. Our language allows the user to define similarity relations and use the approximations induced by them in the definition of other four-valued sets. A positive aspect is that it allows users to tune the level of uncertainty or the source of uncertainty that best suits applications.

[286] Rickard Karlsson, Thomas SchŲn, David TŲrnqvist, Gianpaolo Conte and Fredrik Gustafsson. 2008.
Utilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application.
In Proceedings of ReglermŲte 2008, pages 313–322.
Related report: http://urn.kb.se/resolve?urn=urn:nbn:se:...

This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. Thesecond one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. Using the standard FastSLAM algorithm, only low-dimensional vehicle modelsare computationally feasible. In this work, an algorithm is introduced which merges FastSLAM and MPF, and the result is an algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a UAV (helicopter) are presented. The algorithmfuses measurements from on-board inertial sensors (accelerometer and gyro) and vision in order to solve the SLAM problem, i.e., enable navigation over a long period of time.

[285] Full text  Fredrik Heintz, Mattias Krysander, Jacob Roll and Erik Frisk. 2008.
FlexDx: A Reconfigurable Diagnosis Framework.
In Proceedings of the 19th International Workshop on Principles of Diagnosis (DX).

Detecting and isolating multiple faults is a computationally intense task which typically consists of computing a set of tests, and then computing the diagnoses based on the test results. This paper describes FlexDx, a reconfigurable diagnosis framework which reduces the computational burden by only running the tests that are currently needed. The method selects tests such that the isolation performance of the diagnostic system is maintained. Special attention is given to the practical issues introduced by a reconfigurable diagnosis framework such as FlexDx. For example, tests are added and removed dynamically, tests are partially performed on historic data, and synchronous and asynchronous processing are combined. To handle these issues FlexDx uses DyKnow, a stream-based knowledge processing middleware framework. The approach is exemplified on a relatively small dynamical system, which still illustrates the computational gain with the proposed approach.

[284] Per-Magnus Olsson. 2008.
Practical Pathfinding in Dynamic Environments.
In Steve Rabin, editor, AI Game Programming Wisdom 4. Charles River. ISBN: 978-1-58450-523-5, 158-450-523-0.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/11222031
link: http://www.amazon.com/AI-Game-Programmin...

Welcome to the latest volume of AI Game Programming Wisdom! AI Game Programming Wisdom 4 includes a collection of more than 50 new articles featuring cutting-edge techniques, algorithms, and architectures written by industry professionals for use in commercial game development. Organized into 7 sections, this comprehensive volume explores every important aspect of AI programming to help you develop and expand your own personal AI toolbox. You'll find ready-to-use ideas, algorithms, and code in all key AI areas including general wisdom, scripting and dialogue, movement and pathfinding, architecture, tactics and planning, genre specific, and learning and adaptation. New to this volume are articles on recent advances in realistic agent, squad, and vehicle movement, as well as dynamically changing terrain, as exemplified in such popular games as Company of Heroes.You'll also find information on planning as a key game architecture, as well as important new advances in learning algorithms and player modeling. AI Game Programming Wisdom 4 features coverage of multiprocessor architectures, Bayesian networks, planning architectures, conversational AI, reinforcement learning, and player modeling.These valuable and innovative insights and issues offer the possibility of new game AI experiences and will undoubtedly contribute to taking the games of tomorrow to the next level.

[283] Full text  Piotr Rudol, Mariusz Wzorek, Gianpaolo Conte and Patrick Doherty. 2008.
Micro unmanned aerial vehicle visual servoing for cooperative indoor exploration.
In Proceedings of the IEEE Aerospace Conference. In series: Aerospace Conference Proceedings #2008. IEEE conference proceedings. ISBN: 978-1-4244-1487-1.
DOI: 10.1109/AERO.2008.4526558.

Recent advances in the field of micro unmanned aerial vehicles (MAVs) make flying robots of small dimensions suitable platforms for performing advanced indoor missions. In order to achieve autonomous indoor flight a pose estimation technique is necessary. This paper presents a complete system which incorporates a vision-based pose estimation method to allow a MAV to navigate in indoor environments in cooperation with a ground robot. The pose estimation technique uses a lightweight light emitting diode (LED) cube structure as a pattern attached to a MAV. The pattern is observed by a ground robot's camera which provides the flying robot with the estimate of its pose. The system is not confined to a single location and allows for cooperative exploration of unknown environments. It is suitable for performing missions of a search and rescue nature where a MAV extends the range of sensors of the ground robot. The performance of the pose estimation technique and the complete system is presented and experimental flights of a vertical take-off and landing (VTOL) MAV are described.

[282] Full text  Fredrik Heintz, Jonas KvarnstrŲm and Patrick Doherty. 2008.
Knowledge Processing Middleware.
In S. Carpin, I. Noda, E. Pagello, M. Reggiani and O. von Stryk, editors, Proceedings of the 1st International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), pages 147–158. In series: Lecture Notes in Computer Science #5325. Springer. ISBN: 978-3-540-89075-1, 978-3-540-89076-8.
DOI: 10.1007/978-3-540-89076-8_17.
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

Developing autonomous agents displaying rational and goal-directed behavior in a dynamic physical environment requires the integration of a great number of separate deliberative and reactive functionalities. This integration must be built on top of a solid foundation of data, information and knowledge having numerous origins, including quantitative sensors and qualitative knowledge databases. Processing is generally required on many levels of abstraction and includes refinement and fusion of noisy sensor data and symbolic reasoning. We propose the use of knowledge processing middleware as a systematic approach for organizing such processing. Desirable properties of such middleware are presented and motivated. We then argue that a declarative stream-based system is appropriate to provide the desired functionality. Different types of knowledge processes and components of the middleware are described and motivated in the context of a UAV traffic monitoring application. Finally DyKnow, a concrete example of stream-based knowledge processing middleware, is briefly described.

[281] Oleg Burdakov, Kaj Holmberg and Per-Magnus Olsson. 2008.
A Dual Ascent Method for the Hop-constrained Shortest Path with Application to Positioning of Unmanned Aerial Vehicles.
Technical Report. In series: Report / Department of Mathematics, Universitetet i LinkŲping, Tekniska hŲgskolan #2008:7. LinkŲping University Electronic Press. 30 pages.

We study the problem of positioning unmanned aerial vehicles (UAVs) to maintain an unobstructed flow of communication from a surveying UAV to some base station through the use of multiple relay UAVs. This problem can be modeled as a hopconstrained shortest path problem in a large visibility graph. We propose a dual ascent method for solving this problem, optionally within a branch-and-bound framework. Computational tests show that realistic problems can be solved in a reasonably short time, and that the proposed method is faster than the classical dynamic programming approach.

[280] Full text  Per Nyblom. 2008.
Dynamic Abstraction for Interleaved Task Planning and Execution.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1363. Institutionen fŲr datavetenskap. 94 pages. ISBN: 9789173939058.
Note: Report code: LiU-Tek-Lic-2008:21.
cover: http://liu.diva-portal.org/smash/get/div...

It is often beneficial for an autonomous agent that operates in a complex environment to make use of different types of mathematical models to keep track of unobservable parts of the world or to perform prediction, planning and other types of reasoning. Since a model is always a simplification of something else, there always exists a tradeoff between the model’s accuracy and feasibility when it is used within a certain application due to the limited available computational resources. Currently, this tradeoff is to a large extent balanced by humans for model construction in general and for autonomous agents in particular. This thesis investigates different solutions where such agents are more responsible for balancing the tradeoff for models themselves in the context of interleaved task planning and plan execution. The necessary components for an autonomous agent that performs its abstractions and constructs planning models dynamically during task planning and execution are investigated and a method called DARE is developed that is a template for handling the possible situations that can occur such as the rise of unsuitable abstractions and need for dynamic construction of abstraction levels. Implementations of DARE are presented in two case studies where both a fully and partially observable stochastic domain are used, motivated by research with Unmanned Aircraft Systems. The case studies also demonstrate possible ways to perform dynamic abstraction and problem model construction in practice.

[279] Full text  Anders Lund, Peter Andersson, J. Eriksson, J. Hallin, T. Johansson, R. Jonsson, H. LŲfgren, C. Paulin and A. Tell. 2008.
Automatic fitting procedures for EPR spectra of disordered systems: matrix diagonalization and perturbation methods applied to fluorocarbon radicals.
Spectrochimica Acta Part A - Molecular and Biomolecular Spectroscopy, 69(5):1294–1300. Elsevier.
DOI: 10.1016/j.saa.2007.09.040.
Note: Original publication: A. Lund, P. Andersson, J. Eriksson, J. Hallin, T. Johansson, R. Jonsson, H. Löfgren, C. Paulin and A. Tell, Automatic fitting procedures for EPR spectra of disordered systems: matrix diagonalization and perturbation methods applied to fluorocarbon radicals, 2008, Spectrochimica Acta Part A, (69), 5, 1294-1300. http://dx.doi.org/10.1016/j.saa.2007.09.040. Copyright: Elsevier B.V., http://www.elsevier.com/
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

Two types of automatic fitting procedures for EPR spectra of disordered systems have been developed, one based on matrix diagonalisation of a general spin Hamiltonian, the other on 2<sup>nd</sup> order perturbation theory. The first program is based on a previous Fortran code complemented with a newly written interface in Java to provide user-friendly in- and output. The second is intended for the special case of free radicals with several relatively weakly interacting nuclei, in which case the general method becomes slow. A least squares‚Äô fitting procedure utilizing analytical or numerical derivatives of the theoretically calculated spectrum with respect to the g-and hyperfine structure (hfs) tensors was used to refine those parameters in both cases. ‚ÄėRigid limit‚Äô ESR spectra from radicals in organic matrices and in polymers, previously studied experimentally at low temperature, were analysed by both methods. Fluoro-carbon anion radicals could be simulated, quite accurately with the exact method, whereas automatic fitting on e.g. the c-C<sub>4</sub>F<sub>8</sub><sup>-</sup> anion radical is only feasible with the 2<sup>nd</sup> order approximative treatment. Initial values for the <sup>19</sup>F hfs tensors estimated by DFT calculations were quite close to the final. For neutral radicals of the type XCF<sub>2</sub>CF<sub>2</sub>‚ÄĘ the refinement of the hfs tensors by the exact method worked better than the approximate. The reasons are discussed. The ability of the fitting procedures to recover the correct magnetic parameters of disordered systems was investigated by fittings to synthetic spectra with known hfs tensors. The exact and the approximate methods are concluded to be complementary, one being general, but limited to relatively small systems, the other being a special treatment, suited for S=¬Ĺ systems with several moderately large hfs.

[278] Full text  Heike Joe Steinhauer. 2008.
A Representation Scheme for Description and Reconstruction of Object Configurations Based on Qualitative Relations.
PhD Thesis. In series: LinkŲping Studies in Science and Technology. Dissertations #1204. LinkŲping University Electronic Press. 178 pages. ISBN: 978-91-7393-823-5.
cover: http://liu.diva-portal.org/smash/get/div...

One reason Qualitative Spatial Reasoning (QSR) is becoming increasingly important to Artificial Intelligence (AI) is the need for a smooth ‚Äėhuman-like‚Äô communication between autonomous agents and people. The selected, yet general, task motivating the work presented here is the scenario of an object configuration that has to be described by an observer on the ground using only relational object positions. The description provided should enable a second agent to create a map-like picture of the described configuration in order to recognize the configuration on a representation from the survey perspective, for instance on a geographic map or in the landscape itself while observing it from an aerial vehicle. Either agent might be an autonomous system or a person. Therefore, the particular focus of this work lies on the necessity to develop description and reconstruction methods that are cognitively easy to apply for a person.This thesis presents the representation scheme QuaDRO (Qualitative Description and Reconstruction of Object configurations). Its main contributions are a specification and qualitative classification of information available from different local viewpoints into nine qualitative equivalence classes. This classification allows the preservation of information needed for reconstruction into a global frame of reference. The reconstruction takes place in an underlying qualitative grid with adjustable granularity. A novel approach for representing objects of eight different orientations by two different frames of reference is used. A substantial contribution to alleviate the reconstruction process is that new objects can be inserted anywhere within the reconstruction without the need for backtracking or rereconstructing. In addition, an approach to reconstruct configurations from underspecified descriptions using conceptual neighbourhood-based reasoning and coarse object relations is presented.

2007
[277] Full text  Simone Duranti and Gianpaolo Conte. 2007.
In-flight Identification of the Augmented Flight Dynamics of the Rmax Unmanned Helicopter.
In 17th IFAC Symposium on Automatic Control in Aerospace. International Federation of Automatic Control.
DOI: 10.3182/20070625-5-FR-2916.00038.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

The flight dynamics of the Yamaha RMAX unmanned helicopter has been investigated, and mapped into a six degrees of freedom mathematical model. The model has been obtained by a combined black-box system identification technique and a classic model-based parameter identification approach. In particular, the closed-loop behaviour of the built-in attitude control system has been studied, to support the decision whether to keep it as inner stabilization loop or to develop an own stability augmentation system. The flight test method and the test instrumentation are described in detail; some samples of the flight test data are compared to the model outputs as validation, and an overall assessment of the built-in stabilization system is supplied.

[276] Barbara Dunin-Keplicz and Andrzej Szalas. 2007.
Towards Approximate BGI Systems.
In Proceedings of the 5th International Central and Eastern European Conference on Multi-Agent Systems (CEEMAS), pages 277–287. In series: Lecture Notes in Artificial Intelligence #4696. Springer Berlin/Heidelberg. ISBN: 9783540752530.
DOI: 10.1007/978-3-540-75254-7_28.

This paper focuses on modelling perception and vague concepts in the context of multiagent Bgi (<em>Beliefs, Goals</em> and <em>Intentions</em>) systems. The starting point is the multimodal formalization of such systems. Then we make a shift from Kripke structures to similarity structures, allowing us to model perception and vagueness in an uniform way, ‚Äúcompatible‚ÄĚ with the multimodal approach. As a result we introduce and discuss <em>approximate B</em> <em>gi</em> <em>systems</em>, which can also be viewed as a way to implement multimodal specifications of Bgi systems in the context of perception.

[275] Full text  Thomas Lemaire, Cyrille Berger, Il-Kyun Jung and Simon Lacroix. 2007.
Vision-Based SLAM: Stereo and Monocular Approaches.
International Journal of Computer Vision, 74(3):343–364. Kluwer Academic Publishers.
DOI: 10.1007/s11263-007-0042-3.

Building a spatially consistent model is a key functionality to endow a mobile robot with autonomy. Without an initial map or an absolute localization means, it requires to concurrently solve the localization and mapping problems. For this purpose, vision is a powerful sensor, because it provides data from which stable features can be extracted and matched as the robot moves. But it does not directly provide 3D information, which is a difficulty for estimating the geometry of the environment. This article presents two approaches to the SLAM problem using vision: one with stereovision, and one with monocular images. Both approaches rely on a robust interest point matching algorithm that works in very diverse environments. The stereovision based approach is a classic SLAM implementation, whereas the monocular approach introduces a new way to initialize landmarks. Both approaches are analyzed and compared with extensive experimental results, with a rover and a blimp.

[274] Full text  Karolina Eliasson. 2007.
Case-Based Techniques Used for Dialogue Understanding and Planning in a Human-Robot Dialogue System.
In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence.

[273] Full text  Per Nyblom. 2007.
Dynamic Planning Problem Generation in a UAV Domain.
In 6th IFAC Symposium on Intelligent Autonomous Vehicles (2007) Intelligent Autonomous Vehicles, Volume# 6 | Part# 1, pages 258–263. In series: IFAC Proceedings series #??. Elsevier. ISBN: 978-3-902661-65-4.
DOI: 10.3182/20070903-3-FR-2921.00045.

One of the most successful methods for planning in large partially observable stochastic domains is depth-limited forward search from the current belief state together with a utility estimation. However, when the environment is continuous and the number of possible actions is practically infinite, then abstractions have to be made before any forward search planning can be performed. The paper presents a method to dynamically generate such planning problem abstractions for a domain that is inspired by our research with unmanned aerial vehicles (UAVs). The planning problems are created by first stating the selection of points to fly to as an optimization problem. When the points have been selected, a set of possible paths between them are then created with a pathplanner and then forward search in the belief state space is applied. The method has been implemented and tested in simulation and the experiments show the importance of modelling both the dynamics of the environment and the limited computational resources of the architecture when searching for suitable parameters in the planning problem formulation procedure.

[272] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2007.
Communication between agents with heterogeneous perceptual capabilities.
Information Fusion, 8(1):56–69. Elsevier.
DOI: 10.1016/j.inffus.2005.05.006.

In real world applications robots and software agents often have to be equipped with higher level cognitive functions that enable them to reason, act and perceive in changing, incompletely known and unpredictable environments. One of the major tasks in such circumstances is to fuse information from various data sources. There are many levels of information fusion, ranging from the fusing of low level sensor signals to the fusing of high level, complex knowledge structures. In a dynamically changing environment even a single agent may have varying abilities to perceive its environment which are dependent on particular conditions. The situation becomes even more complex when different agents have different perceptual capabilities and need to communicate with each other. In this paper, we propose a framework that provides agents with the ability to fuse both low and high level approximate knowledge in the context of dynamically changing environments while taking account of heterogeneous and contextually limited perceptual capabilities. To model limitations on an agent's perceptual capabilities we introduce the idea of partial tolerance spaces. We assume that each agent has one or more approximate databases where approximate relations are represented using lower and upper approximations on sets. Approximate relations are generalizations of rough sets. It is shown how sensory and other limitations can be taken into account when constructing and querying approximate databases for each respective agent. Complex relations inherit the approximativeness of primitive relations used in their definitions. Agents then query these databases and receive answers through the filters of their perceptual limitations as represented by (partial) tolerance spaces and approximate queries. The techniques used are all tractable. © 2005 Elsevier B.V. All rights reserved.

[271] Full text  D.M. Gabbay and Andrzej Szalas. 2007.
Second-order quantifier elimination in higher-order contexts with applications to the semantical analysis of conditionals.
Studia Logica: An International Journal for Symbolic Logic, 87(1):37–50. Springer.
DOI: 10.1007/s11225-007-9075-4.

Second-order quantifier elimination in the context of classical logic emerged as a powerful technique in many applications, including the correspondence theory, relational databases, deductive and knowledge databases, knowledge representation, commonsense reasoning and approximate reasoning. In the current paper we first generalize the result of Nonnengart and Szalas [17] by allowing second-order variables to appear within higher-order contexts. Then we focus on a semantical analysis of conditionals, using the introduced technique and Gabbay's semantics provided in [10] and substantially using a third-order accessibility relation. The analysis is done via finding correspondences between axioms involving conditionals and properties of the underlying third-order relation. © 2007 Springer Science+Business Media B.V.

[270] Full text  Patrick Doherty and Andrzej Szalas. 2007.
A correspondence framework between three-valued logics and similarity-based approximate reasoning.
Fundamenta Informaticae, 75(1-4):179–193. IOS Press.

This paper focuses on approximate reasoning based on the use of similarity spaces. Similarity spaces and the approximated relations induced by them are a generalization of the rough set-based approximations of Pawlak [17, 18]. Similarity spaces are used to define neighborhoods around individuals and these in turn are used to define approximate sets and relations. In any of the approaches, one would like to embed such relations in an appropriate logic which can be used as a reasoning engine for specific applications with specific constraints. We propose a framework which permits a formal study of the relationship between approximate relations, similarity spaces and three-valued logics. Using ideas from correspondence theory for modal logics and constraints on an accessibility relation, we develop an analogous framework for three-valued logics and constraints on similarity relations. In this manner, we can provide a tool which helps in determining the proper three-valued logical reasoning engine to use for different classes of approximate relations generated via specific types of similarity spaces. Additionally, by choosing a three-valued logic first, the framework determines what constraints would be required on a similarity relation and the approximate relations induced by it. Such information would guide the generation of approximate relations for specific applications.

[269] David Lawrence, Erik Sandewall and Peter Berkesand. 2007.
A Swedish Journal Publication Service.
In HŲgskolor och samhšlle i samverkan (HSS).

In 2002, Linköping University Electronic Press began development of a journal article reviewing support system (JARSS) as a tool for Editors of electronic journals. The system-s database contains submitted articles, abstracts and other secondary information, reviews, and e-mail communication for the purpose of submission, reviewing and final acceptance. The interface maintains a log of all events pertaining to the article and the associated status changes. The successive status options of an article (received, under review, conditional accept, etc.) correspond to the editorial workflow. JARRS has been used since its inception to run the Artificial Intelligence Journal (AIJ), an Elsevier publication. In essence a service is offered to take care of the technical aspects of journal publication, allowing editors more time to solicit papers of high quality.

[268] Mariusz Wzorek and Patrick Doherty. 2007.
A framework for reconfigurable path planning for autonomous unmanned aerial vehicles.
Manuscript (preprint).

[267] Full text  Simone Duranti, Gianpaolo Conte, David LundstrŲm, Piotr Rudol, Mariusz Wzorek and Patrick Doherty. 2007.
LinkMAV, a prototype rotary wing micro aerial vehicle.
In 17th IFAC Symposium on Automatic Control in Aerospace,2007. Elsevier.

[266] Patrick Doherty, Barbara Dunin-Keplicz and Andrzej Szalas. 2007.
Dynamics of approximate information fusion.
In Proceedings of the International Conference on Rough Sets and Emerging Intelligent Systems Paradigms (RSEISP), pages 668–677. In series: Lecture Notes in Artificial Intelligence #4585. Springer Berlin/Heidelberg. ISBN: 978-3-540-73450-5.
DOI: 10.1007/978-3-540-73451-2_70.

The multi-agent system paradigm has proven to be a useful means of abstraction when considering distributed systems with interacting components. It is often the case that each component may be viewed as an intelligent agent with specific and often limited perceptual capabilities. It is also the case that these agent components may be used as information sources and such sources may be aggregated to provide global information about particular states, situations or activities in the embedding environment. This paper investigates a framework for information fusion based on the use of generalizations of rough set theory and the use of dynamic logic as a basis for aggregating similarity relations among objects where the similarity relations represent individual agents perceptual capabilities or limitations. As an added benefit, it is shown how this idea may also be integrated into description logics.

[265] Patrick Doherty and John-Jules Meyer. 2007.
Towards a delegation framework for aerial robotic mission scenarios.
In Proceedings of the 11th International Workshop on Cooperative Information Agents (CIA), pages 5–26. Springer Berlin/Heidelberg. ISBN: 978-3-540-75118-2.
DOI: 10.1007/978-3-540-75119-9_2.

The concept of delegation is central to an understanding of the interactions between agents in cooperative agent problem-solving contexts. In fact, the concept of delegation offers a means for studying the formal connections between mixed-initiative problem-solving, adjustable autonomy and cooperative agent goal achievement. In this paper, we present an exploratory study of the delegation concept grounded in the context of a relatively complex multi-platform Unmanned Aerial Vehicle (UAV) catastrophe assistance scenario, where UAVs must cooperatively scan a geographic region for injured persons. We first present the scenario as a case study, showing how it is instantiated with actual UAV platforms and what a real mission implies in terms of pragmatics. We then take a step back and present a formal theory of delegation based on the use of 2APL and KARO. We then return to the scenario and use the new theory of delegation to formally specify many of the communicative interactions related to delegation used in achieving the goal of cooperative UAV scanning. The development of theory and its empirical evaluation is integrated from the start in order to ensure that the gap between this evolving theory of delegation and its actual use remains closely synchronized as the research progresses. The results presented here may be considered a first iteration of the theory and ideas.

[264] Full text  Patrick Doherty and Piotr Rudol. 2007.
A UAV search and rescue scenario with human body detection and geolocalization.
In Proceedings of the 20th Australian Joint Conference on Artificial Intelligence (AI). Springer Berlin/Heidelberg. ISBN: 978-3-540-76926-2.

The use of Unmanned Aerial Vehicles (UAVs) which can operate autonomously in dynamic and complex operational environments is becoming increasingly more common. The UAVTech Lab, is pursuing a long term research endeavour related to the development of future aviation systems which try and push the envelope in terms of using and integrating high-level deliberative or AI functionality with traditional reactive and control components in autonomous UAV systems. In order to carry on such research, one requires challenging mission scenarios which force such integration and development. In this paper, one of these challenging emergency services mission scenarios is presented. It involves search and rescue for injured civilians by UAVs. In leg I of the mission, UAVs scan designated areas and try to identify injured civilians. In leg II of the mission, an attempt is made to deliver medical and other supplies to identified victims. We show how far we have come in implementing and executing such a challenging mission in realistic urban scenarios.

[263] Full text  Luis Mejias, Pascual Campoy, IvŠn F. Mondragůn and Patrick Doherty. 2007.
Stereo visual system for autonomous air vehicle navigation.
In 6th IFAC Symposium on Intelligent Autonomous Vehicles (2007) Intelligent Autonomous Vehicles, Volume# 6 | Part# 1, pages 203–208. In series: IFAC Proceedings series #??. Elsevier. ISBN: 978-3-902661-65-4.
DOI: 10.3182/20070903-3-FR-2921.00037.

We present a system to estimate the altitude and motion of an aerial vehicle using a stereo visual system. The system has been initially tested on a ground robot and the novelty lays on its application and robustness validation in an UAV, where vibrations and rapid environmental changes take place. The two main functionalities are height estimation and visual odometry. The system first detects and tracks salient points in the scene. Depth to the plane containing the features is calculated matching features between left and right images then using the disparity principle. Motion is recovered tracking pixels from one frame to the next one finding its visual displacement and resolving camera rotation and translation by a least-square method. We present results from different experimental trials on the two platforms comparing and discussing the results regarding the trajectories calculated by the visual odometry and the onboard helicopter state estimation.

[262] Full text  Fredrik Heintz, Piotr Rudol and Patrick Doherty. 2007.
From Images to Traffic Behavior - A UAV Tracking and Monitoring Application.
In Proceedings of the 10th International Conference on Information Fusion (FUSION). IEEE conference proceedings. ISBN: 978-0-662-45804-3, 978-0-662-47830-0.
DOI: 10.1109/ICIF.2007.4408103.
Link: http://www.ida.liu.se/~frehe/publication...

An implemented system for achieving high level situation awareness about traffic situations in an urban area is described. It takes as input sequences of color and thermal images which are used to construct and maintain qualitative object structures and to recognize the traffic behavior of the tracked vehicles in real time. The system is tested both in simulation and on data collected during test flights. To facilitate the signal to symbol transformation and the easy integration of the streams of data from the sensors with the GIS and the chronicle recognition system, DyKnow, a stream-based knowledge processing middleware, is used. It handles the processing of streams, including the temporal aspects of merging and synchronizing streams, and provides suitable abstractions to allow high level reasoning and narrow the sense reasoning gap.

[261] Jan Maluszynski, Andrzej Szalas and Aida Vitoria. 2007.
A Four-Valued Logic for Rough Set-Like Approximate Reasoning.
In James F. Peters, Andrzej Skowron, Ivo D√ľntsch, Jerzy Grzymala-Busse, Ewa Orlowska and Lech Polkowski, editors, Transactions on Rough Sets VI, pages 176–190. In series: Lecture Notes in Computer Science #4374/2007. Springer. ISBN: 3-540-71198-8, 978-3-540-71198-8.
DOI: 10.1007/978-3-540-71200-8_11.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/11381912

Annotation The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume VI of the Transactions on Rough Sets (TRS) commemorates the life and work of Zdzislaw Pawlak (1926-2006). His legacy is rich and varied. Prof. Pawlak's research contributions have had far-reaching implications inasmuch as his works are fundamental in establishing new perspectives for scientific research in a wide spectrum of fields. This volume of the TRS presents papers that reflect the profound influence of a number of research initiatives by Professor Pawlak. In particular, this volume introduces a number of new advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science. These advances have significant implications in a number of research areas such as the foundations of rough sets, approximate reasoning, bioinformatics, computational intelligence, cognitive science, data mining, information systems, intelligent systems, machine intelligence, and security.

[260] Full text  Fredrik Heintz, Piotr Rudol and Patrick Doherty. 2007.
Bridging the Sense-Reasoning Gap Using DyKnow: A Knowledge Processing Middleware Framework.
In Joachim Hertzberg, Michael Beetz and Roman Englert, editors, Proceedings of the 30th Annual German Conference on Artificial Intelligence (KI), pages 460–463. In series: Lecture Notes in Computer Science #4667. Springer. ISBN: 978-3-540-74564-8.
DOI: 10.1007/978-3-540-74565-5_40.
Link: http://www.ida.liu.se/~frehe/publication...

To achieve complex missions an autonomous unmanned aerial vehicle (UAV) operating in dynamic environments must have and maintain situational awareness. This can be achieved by continually gathering information from many sources, selecting the relevant information for current tasks, and deriving models about the environment and the UAV itself. It is often the case models suitable for traditional control, are not sufficient for deliberation. The need for more abstract models creates a sense-reasoning gap. This paper presents DyKnow, a knowledge processing middleware framework, and shows how it supports bridging the gap in a concrete UAV traffic monitoring application. In the example, sequences of color and thermal images are used to construct and maintain qualitative object structures. They model the parts of the environment necessary to recognize traffic behavior of tracked vehicles in real-time. The system has been implemented and tested in simulation and on data collected during flight tests.

[259] Full text  Martin Magnusson and Patrick Doherty. 2007.
Deductive Planning with Temporal Constraints.
In Commonsense 2007, the 8th International Symposium on Logical Formalizations of Commonsense Reasoning,2007. AAAI Press. ISBN: 978-1-57735-314-0.
Link: http://www.ucl.ac.uk/commonsense07/paper...

Temporal Action Logic is a well established logical formalism for reasoning about action and change using an explicit time representation that makes it suitable for applications that involve complex temporal reasoning. We take advantage of constraint satisfaction technology to facilitate such reasoning through temporal constraint networks. Extensions are introduced that make generation of action sequences possible, thus paving the road for interesting applications in deductive planning. The extended formalism is encoded as a logic program that is able to realize a least commitment strategy that generates partial order plans in the context of both qualitative and quantitative temporal constraints.

[258] BjŲrn Hšgglund. 2007.
A framework for designing constraint stores.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1302. LinkŲpings universitet. 118 pages. ISBN: 9789185715701.

A constraint solver based on concurrent search and propagation provides a well-defined component model for propagators by enforcing a strict two-level architecture. This makes it straightforward for third parties to invent, implement and deploy new kinds of propagators. The most critical components of such solvers are the constraint stores through which propagators communicate with each other. Introducing stores supporting new kinds of stored constraints can potentially increase the solving power by several orders of magnitude. This thesis presents a theoretical framework for designing stores achieving this without loss of propagator interoperability.

[257] Full text  Gianpaolo Conte. 2007.
Navigation Functionalities for an Autonomous UAV Helicopter.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1307. LinkŲping University Electronic Press. 107 pages. ISBN: 9789185715350.

This thesis was written during the WITAS UAV Project where one of the goals has been the development of a software/hardware architecture for an unmanned autonomous helicopter, in addition to autonomous functionalities required for complex mission scenarios. The algorithms developed here have been tested on an unmanned helicopter platform developed by Yamaha Motor Company called the RMAX. The character of the thesis is primarily experimental and it should be viewed as developing navigational functionality to support autonomous flight during complex real world mission scenarios. This task is multidisciplinary since it requires competence in aeronautics, computer science and electronics. The focus of the thesis has been on the development of a control method to enable the helicopter to follow 3D paths. Additionally, a helicopter simulation tool has been developed in order to test the control system before flight-tests. The thesis also presents an implementation and experimental evaluation of a sensor fusion technique based on a Kalman filter applied to a vision based autonomous landing problem. Extensive experimental flight-test results are presented.

[256] Full text  Martin Magnusson. 2007.
Deductive Planning and Composite Actions in Temporal Action Logic.
Licentiate Thesis. In series: LinkŲping Studies in Science and Technology. Thesis #1329. Institutionen fŲr datavetenskap. 86 pages. ISBN: 9789185895939.
cover: http://liu.diva-portal.org/smash/get/div...

Temporal Action Logic is a well established logical formalism for reasoning about action and change that has long been used as a formal specification language. Its first-order characterization and explicit time representation makes it a suitable target for automated theorem proving and the application of temporal constraint solvers. We introduce a translation from a subset of Temporal Action Logic to constraint logic programs that takes advantage of these characteristics to make the logic applicable, not just as a formal specification language, but in solving practical reasoning problems. Extensions are introduced that enable the generation of action sequences, thus paving the road for interesting applications in deductive planning. The use of qualitative temporal constraints makes it possible to follow a least commitment strategy and construct partially ordered plans. Furthermore, the logical language and logic program translation is extended with the notion of composite actions that can be used to formulate and execute scripted plans with conditional actions, non-deterministic choices, and loops. The resulting planner and reasoner is integrated with a graphical user interface in our autonomous helicopter research system and applied to logistics problems. Solution plans are synthesized together with monitoring constraints that trigger the generation of recovery actions in cases of execution failures.

2006
[255] Ewa Orlowska, Alberto Policriti and Andrzej Szalas. 2006.
Algebraic and Relational Deductive Tools.
Conference Proceedings. In series: Journal of Applied Non-Classical Logics #??. …ditions HermŤs-Lavoisier.
Note: Special Issue

[254] Full text  Alexander Kleiner, Christian Dornhege, Rainer KŁmmerle, Michael Ruhnke, Bastian Steder, Bernhard Nebel, Patrick Doherty, Mariusz Wzorek, Piotr Rudol, Gianpaolo Conte, Simone Duranti and David LundstrŲm. 2006.
RoboCupRescue - Robot League Team RescueRobots Freiburg (Germany).
In RoboCup 2006 (CDROM Proceedings), Team Description Paper, Rescue Robot League.
Note: (1st place in the autonomy competition)
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

This paper describes the approach of the RescueRobots Freiburg team, which is a team of students from the University of Freiburg that originates from the former CS Freiburg team (RoboCupSoccer) and the ResQ Freiburg team (RoboCupRescue Simulation). Furthermore we introduce linkMAV, a micro aerial vehicle platform. Our approach covers RFID-based SLAM and exploration, autonomous detection of relevant 3D structures, visual odometry, and autonomous victim identification. Furthermore, we introduce a custom made 3D Laser Range Finder (LRF) and a novel mechanism for the active distribution of RFID tags.

[253] Erik Sandewall. 2006.
Systems - Opening up the process.
Nature, ??(??):????. Nature Publishing Group.
DOI: 10.1038/nature04994.

n/a

[252] Full text  Per Nyblom. 2006.
Dynamic Abstraction for Hierarchical Problem Solving and Execution in Stochastic Dynamic Environments.
In Loris Penserini, Pavlos Peppas, Anna Perini, editors, STAIRS 2006, pages 263–264. In series: Frontiers in Artificial Intelligence and Applications #142. IOS Press. ISBN: 978-1-58603-645-4, e-978-1-60750-190-9.
Link to publication: http://www.booksonline.iospress.nl/Conte...

Most of today’s autonomous problem solving agents perform their task with the help of problem domain specifications that keep their abstractions fixed. Those abstractions are often selected by human users. We think that the approach with fixed-abstraction domain specifications is very inflexible because it does not allow the agent to focus its limited computational resources on what may be most relevant at the moment. We would like to build agents that dynamically find suitable abstractions depending on relevance for their current task and situation. This idea of dynamic abstraction has recently been considered an important research problem within the area of hierarchical reinforcement learning [1].

[251] Full text  Torsten Merz, Simone Duranti and Gianpaolo Conte. 2006.
Autonomous landing of an unmanned helicopter based on vision and inertial sensing.
In Marcelo H. Ang and Oussama Khatib, editors, Proceedings of the 9th International Symposium on Experimental Robotics, pages 343–352. In series: Springer Tracts in Advanced Robotics #21. Springer. ISBN: 978-3-540-28816-9.
DOI: 10.1007/11552246_33.
Link to Ph.D. Thesis: http://urn.kb.se/resolve?urn=urn:nbn:se:...

In this paper we propose an autonomous precision landing method for an unmanned helicopter based on an on-board visual navigation system consisting of a single pan-tilting camera, off-the-shelf computer hardware and inertial sensors. Compared to existing methods, the system doesn't depend on additional sensors (in particular not on GPS), offers a wide envelope of starting points for the autonomous approach, and is robust to different weather conditions. Helicopter position and attitude is estimated from images of a specially designed landing pad. We provide results from both simulations and flight tests, showing the performance of the vision system and the overall quality of the landing. © Springer-Verlag Berlin/Heidelberg 2006.

[250] Full text  Patrik Haslum. 2006.
Improving heuristics through relaxed search - An analysis of TP4 and HSP*a in the 2004 planning competition.
The journal of artificial intelligence research, 25(??):233–267. AAAI Press.
DOI: 10.1613/jair.1885.

The h(m) admissible heuristics for (sequential and temporal) regression planning are defined by a parameterized relaxation of the optimal cost function in the regression search space, where the parameter m offers a trade-off between the accuracy and computational cost of the heuristic. Existing methods for computing the h(m) heuristic require time exponential in m, limiting them to small values (m &lt;= 2). The h(m) heuristic can also be viewed as the optimal cost function in a relaxation of the search space: this paper presents relaxed search, a method for computing this function partially by searching in the relaxed space. The relaxed search method, because it compute h(m) only partially, is computationally cheaper and therefore usable for higher values of m. The (complete) h(2) heuristic is combined with partial hm heuristics , for m = 3, ... computed by relaxed search, resulting in a more accurate heuristic. This use of the relaxed search method to improve on the h(2) heuristic is evaluated by comparing two optimal temporal planners: TP4, which does not use it, and HSP*(a), which uses it but is otherwise identical to TP4. The comparison is made on the domains used in the 2004 International Planning Competition, in which both planners participated. Relaxed search is found to be cost effective in some of these domains, but not all. Analysis reveals a characterization of the domains in which relaxed search can be expected to be cost effective, in terms of two measures on the original and relaxed search spaces. In the domains where relaxed search is cost effective, expanding small states is computationally cheaper than expanding large states and small states tend to have small successor states.

[249] Klas Nordberg, Patrick Doherty, Per-Erik Forssťn, Johan Wiklund and Per Andersson. 2006.
A flexible runtime system for image processing in a distributed computational environment for an unmanned aerial vehicle.
International Journal of Pattern Recognition and Artificial Intelligence, 20(5):763–780.
DOI: 10.1142/S0218001406004867.

A runtime system for implementation of image processing operations is presented. It is designed for working in a flexible and distributed environment related to the software architecture of a newly developed UAV system. The software architecture can be characterized at a coarse scale as a layered system, with a deliberative layer at the top, a reactive layer in the middle, and a processing layer at the bottom. At a finer scale each of the three levels is decomposed into sets of modules which communicate using CORBA, allowing system development and deployment on the UAV to be made in a highly flexible way. Image processing takes place in a dedicated module located in the process layer, and is the main focus of the paper. This module has been designed as a runtime system for data flow graphs, allowing various processing operations to be created online and on demand by the higher levels of the system. The runtime system is implemented in Java, which allows development and deployment to be made on a wide range of hardware/software configurations. Optimizations for particular hardware platforms have been made using Java's native interface.

[248] Full text  Andrzej Szalas and Jerzy Tyszkiewicz. 2006.
On the fixpoint theory of equality and its applications.
In Proceedings of the 9th International Conference on Relational Methods in Computer Science and 4th International Workshop on Applications of Kleene Algebra (RelMiCS/AKA), pages 388–401. In series: Lecture Notes in Computer Science #4136. Springer.
DOI: 10.1007/11828563_26.

In the current paper we first show that the fixpoint theory of equality is decidable. The motivation behind considering this theory is that second-order quantifier elimination techniques based on a theorem given in [16], when successful, often result in such formulas. This opens many applications, including automated theorem. proving, static verification of integrity constraints in databases as well as reasoning with weakest sufficient and strongest necessary conditions.

[247] Full text  Erik Johan Sandewall. 2006.
Coordination of actions in an autonomous robotic system.
In Oliviero Stock, Marco Schaerf, editors, Reasoning, Action and Interaction in AI Theories and Systems: Essays Dedicated to Luigia Carlucci Aiello, pages 177–191. In series: Lecture Notes in Computer Science #4155. Springer. ISBN: 978-3-5403-7901-0, 978-3-5403-7902-7.
DOI: 10.1007/11829263_10.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/11430167
link: http://www.amazon.com/Reasoning-Action-I...

The present book is a festschrift in honor of Luigia Carlucci Aiello. The 18 articles included are written by former students, friends, and international colleagues, who have cooperated with Luigia Carlucci Aiello, scientifically or in AI boards or committees. The contributions by reputed researchers span a wide range of AI topics and reflect the breadth and depth of Aiello's own work

[246] Per Olof Pettersson and Patrick Doherty. 2006.
Probabilistic roadmap based path planning for an autonomous unmanned helicopter.
Journal of Intelligent & Fuzzy Systems, 17(4):395–405. IOS Press.

The emerging area of intelligent unmanned aerial vehicle (UAV) research has shown rapid development in recent years and offers a great number of research challenges for artificial intelligence. For both military and civil applications, there is a desire to develop more sophisticated UAV platforms where the emphasis is placed on development of intelligent capabilities. Imagine a mission scenario where a UAV is supplied with a 3D model of a region containing buildings and road structures and is instructed to fly to an arbitrary number of building structures and collect video streams of each of the building's respective facades. In this article, we describe a fully operational UAV platform which can achieve such missions autonomously. We focus on the path planner integrated with the platform which can generate collision free paths autonomously during such missions. Both probabilistic roadmap-based (PRM) and rapidly exploring random trees-based (RRT) algorithms have been used with the platform. The PRM-based path planner has been tested together with the UAV platform in an urban environment used for UAV experimentation.

[245] Full text  Fredrik Heintz and Patrick Doherty. 2006.
A knowledge processing middleware framework and its relation to the JDL data fusion model.
Journal of Intelligent & Fuzzy Systems, 17(4):335–351. IOS Press.

Any autonomous system embedded in a dynamic and changing environment must be able to create qualitative knowledge and object structures representing aspects of its environment on the fly from raw or preprocessed sensor data in order to reason qualitatively about the environment and to supply such state information to other nodes in the distributed network in which it is embedded. These structures must be managed and made accessible to deliberative and reactive functionalities whose successful operation is dependent on being situationally aware of the changes in both the robotic agent's embedding and internal environments. DyKnow is a knowledge processing middleware framework which provides a set of functionalities for contextually creating, storing, accessing and processing such structures. The framework is implemented and has been deployed as part of a deliberative/reactive architecture for an autonomous unmanned aerial vehicle. The architecture itself is distributed and uses real-time CORBA as a communications infrastructure. We describe the system and show how it can be used to create more abstract entity and state representations of the world which can then be used for situation awareness by an unmanned aerial vehicle in achieving mission goals. We also show that the framework is a working instantiation of many aspects of the JDL data fusion model.

[244] Patrick Doherty, John Mylopoulos and Christopher Welty. 2006.
Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning.
Conference Proceedings. AAAI Press. ISBN: 978-1-57735-281-5.

he National Conference on Artificial Intelligence remains the bellwether for research in artificial intelligence. Leading AI researchers and practitioners as well as scientists and engineers in related fields present theoretical, experimental, and empirical results, covering a broad range of topics that include principles of cognition, perception, and action; the design, application, and evaluation of AI algorithms and systems; architectures and frameworks for classes of AI systems; and analyses of tasks and domains in which intelligent systems perform. The Innovative Applications of Artificial Intelligence conference highlights successful applications of AI technology; explores issues, methods, and lessons learned in the development and deployment of AI applications; and promotes an interchange of ideas between basic and applied AI. This volume presents the proceedings of the latest conferences, held in July, 2006.

[243] Full text  Martin Magnusson and Patrick Doherty. 2006.
Deductive Planning with Temporal Constraints using TAL.
In Proceedings of the International Symposium on Practical Cognitive Agents and Robots (PCAR). UWA Press. ISBN: 1-74052-130-7.
DOI: 10.1145/1232425.1232444.

Temporal Action Logic is a well established logical formalism for reasoning about action and change using an explicit time representation that makes it suitable for applications that involve complex temporal reasoning. We take advantage of constraint satisfaction technology to facilitate such reasoning through temporal constraint networks. Extensions are introduced that make generation of action sequences possible, thus paving the road for interesting applications in deductive planning. The extended formalism is encoded as a logic program that is able to realize a least commitment strategy that generates partial order plans in the context of both qualitative and quantitative temporal constraints.

[242] David D. Woods and Erik Hollnagel. 2006.
Joint cognitive systems: Patterns in cognitive systems engineering.
Book. CRC/Taylor & Francis. 232 pages. ISBN: 978-0-8493-3933-2, 0-8493-3933-2.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/hitlist?d=libris&q=9...
link: http://www.amazon.com/Joint-Cognitive-Sy...

Our fascination with new technologies is based on the assumption that more powerful automation will overcome human limitations and make our systems 'faster, better, cheaper,' resulting in simple, easy tasks for people. But how does new technology and more powerful automation change our work? Research in Cognitive Systems Engineering (CSE) looks at the intersection of people, technology, and work. What it has found is not stories of simplification through more automation, but stories of complexity and adaptation. When work changed through new technology, practitioners had to cope with new complexities and tighter constraints. They adapted their strategies and the artifacts to work around difficulties and accomplish their goals as responsible agents. The surprise was that new powers had transformed work, creating new roles, new decisions, and new vulnerabilities. Ironically, more autonomous machines have created the requirement for more sophisticated forms of coordination across people, and across people and machines, to adapt to new demands and pressures. This book synthesizes these emergent Patterns though stories about coordination and mis-coordination, resilience and brittleness, affordance and clumsiness in a variety of settings, from a hospital intensive care unit, to a nuclear power control room, to a space shuttle control center. The stories reveal how new demands make work difficult, how people at work adapt but get trapped by complexity, and how people at a distance from work oversimplify their perceptions of the complexities, squeezing practitioners. The authors explore how CSE observes at the intersection of people, technology, and work, how CSE abstracts patterns behind the surface details and wide variations, and how CSE discovers promising new directions to help people cope with complexities. The stories of CSE show that one key to well-adapted work is the ability to be prepared to be surprised. Are you ready?

[241] Andrzej Szalas. 2006.
Second-order Reasoning in Description Logics.
Journal of applied non-classical logics, 16(3 - 4):517–530. …ditions HermŤs-Lavoisier.
DOI: 10.3166/jancl.16.517-530.

Description logics refer to a family of formalisms concentrated around concepts, roles and individuals. They belong to the most frequently used knowledge representation formalisms and provide a logical basis to a variety of well known paradigms. The main reasoning tasks considered in the area of description logics are those reducible to subsumption. On the other hand, any knowledge representation system should be equipped with a more advanced reasoning machinery. Therefore in the current paper we make a step towards integrating description logics with second-order reasoning. One of the important motivations behind introducing second-order formalism follows from the fact that many forms of commonsense and nonmonotonic reasoning used in AI can be modelled within the second-order logic. To achieve our goal we first extend description logics with a possibility to quantify over concepts. Since one of the main criticisms against the use of second-order formalisms is their complexity, we next propose second-order quantifier elimination techniques applicable to a large class of description logic formulas. Finally we show applications of the techniques, in particular in reasoning with circumscribed concepts and approximated terminological formulas.

[240] Full text  Mariusz Wzorek, David Landťn and Patrick Doherty. 2006.
GSM Technology as a Communication Media for an Autonomous Unmanned Aerial Vehicle.
In Proceedings of the 21st Bristol International UAV Systems Conference (UAVS). University of Bristol, Department of Aerospace engineering. ISBN: 0-9552644-0-5.
Note: ISBN: 0-9552644-0-5

[239] Full text  Martin Magnusson. 2006.
Natural Language Understanding using Temporal Action Logic.
In Proceedings of the Workshop on Knowledge and Reasoning for Language Processing (KRAQ). Association for Computational Linguistics.

We consider a logicist approach to natural language understanding based on the translation of a quasi-logical form into a temporal logic, explicitly constructed for the representation of action and change, and the subsequent reasoning about this semantic structure in the context of a background knowledge theory using automated theorem proving techniques. The approach is substantiated through a proof-of-concept question answering system implementation that uses a head-driven phrase structure grammar developed in the Linguistic Knowledge Builder to construct minimal recursion semantics structures which are translated into a Temporal Action Logic where both the SNARK automated theorem prover and the Allegro Prolog logic programming environment can be used for reasoning through an interchangeable compilation into first-order logic or logic programs respectively.

[238] Full text  H.Joe Steinhauer. 2006.
Qualitative Reconstruction and Update of an Object Constellation.
In Proceedings of the Spatial and Temporal Reasoning Workshop at the 17th European Conference on Artificial Intelligence (ECAI).

We provide a technique for describing, reconstructing and updating an object constellation of moving objects. The relations between the constituent objects, in particular axis-parallel and diagonal relations, are verbally expressed using the double cross method for qualitatively characterizing relations between pairs of objects. The same underlying representation is used to reconstruct the constellation from the given description.

[237] Full text  H.Joe Steinhauer. 2006.
Qualitative Communication about Object Scenes.
In Proceedings of the 29th Annual German Conference on Artificial Intelligence (KI).

[236] Full text  Mariusz Wzorek, Gianpaolo Conte, Piotr Rudol, Torsten Merz, Simone Duranti and Patrick Doherty. 2006.
From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle.
In Proceedings of the 21st Bristol UAV Systems Conference (UAVS).
Link to Ph.D. Thesis: http://urn.kb.se/resolve?urn=urn:nbn:se:...

The use of Unmanned Aerial Vehicles (UAVs) which can operate autonomously in dynamic and complex operational environments is becoming increasingly more common. While the application domains in which they are currently used are still predominantly military in nature, in the future we can expect wide spread usage in thecivil and commercial sectors. In order to insert such vehicles into commercial airspace, it is inherently important that these vehicles can generate collision-free motion plans and also be able to modify such plans during theirexecution in order to deal with contingencies which arise during the course of operation. In this paper, wepresent a fully deployed autonomous unmanned aerial vehicle, based on a Yamaha RMAX helicopter, whichis capable of navigation in urban environments. We describe a motion planning framework which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Treestogether with a path following controller that is used during path execution. Integrating deliberative services, suchas planners, seamlessly with control components in autonomous architectures is currently one of the major open problems in robotics research. We show how the integration between the motion planning framework and thecontrol kernel is done in our system.Additionally, we incorporate a dynamic path reconfigurability scheme. It offers a surprisingly efficient method for dynamic replanning of a motion plan based on unforeseen contingencies which may arise during the execution of a plan. Those contingencies can be inserted via ground operator/UAV interaction to dynamically change UAV flight paths on the fly. The system has been verified through simulation and in actual flight. We present empirical results of the performance of the framework and the path following controller.

[235] Full text  Torsten Merz, Piotr Rudol and Mariusz Wzorek. 2006.
Control System Framework for Autonomous Robots Based on Extended State Machines.
In Proceedings of the International Conference on Autonomic and Autonomous Systems (ICAS).

[234] Full text  Mariusz Wzorek and Patrick Doherty. 2006.
The WITAS UAV Ground System Interface Demonstration with a Focus on Motion and Task Planning.
In Software Demonstrations at the International Conference on Automated Planning Scheduling (ICAPS-SD), pages 36–37.

The Autonomous UAV Technologies Laboratory at Linköping University, Sweden, has been developing fully autonomous rotor-based UAV systems in the mini- and micro-UAV class. Our current system design is the result of an evolutionary process based on many years of developing, testing and maintaining sophisticated UAV systems. In particular, we have used the Yamaha RMAX helicopter platform(Fig. 1) and developed a number of micro air vehicles from scratch.

[233] Full text  Mariusz Wzorek and Patrick Doherty. 2006.
Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle.
In Derek Long, Stephen F. Smith, Daniel Borrajo, Lee McCluskey, editors, Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS), pages 438–441. AAAI Press. ISBN: 978-1-57735-270-9.

In this paper, we present a motion planning framework for a fully deployed autonomous unmanned aerial vehicle which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Trees. Additionally, we incorporate dynamic reconfigurability into the framework by integrating the motion planners with the control kernel of the UAV in a novel manner with little modification to the original algorithms. The framework has been verified through simulation and in actual flight. Empirical results show that these techniques used with such a framework offer a surprisingly efficient method for dynamically reconfiguring a motion plan based on unforeseen contingencies which may arise during the execution of a plan. The framework is generic and can be used for additional platforms.

[232] Full text  Mariusz Wzorek and Patrick Doherty. 2006.
Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle.
In ICHIT 2006 - International Conference on Hybrid Information Technology,2006.

[231] BjŲrn Hšgglund and Anders Haraldsson. 2006.
The Art and Virtue of Symbolic Constraint Propagation.
In CP 2006 Twelfth International Conference on Principles and Practice of Constraint Programming,2006.

[230] Ewa Orlowska and Andrzej Szalas. 2006.
Quantifier Elimination in Elementary Set Theory.
In W. MacCaull, I. Duentsch, M. Winter, editors, Proceedings of the 8th International Conference on Relational Methods in Computer Science (RelMiCS), pages 237–248. In series: Lecture Notes in Computer Science #3929. Springer Berlin/Heidelberg.
DOI: 10.1007/11734673_19.

In the current paper we provide two methods for quantifier elimination applicable to a large class of formulas of the elementary set theory. The first one adapts the Ackermann method [1] and the second one adapts the fixpoint method of [20]. We show applications of the proposed techniques in the theory of correspondence between modal logics and elementary set theory. The proposed techniques can also be applied in an automated generation of proof rules based on the semantic-based translation of axioms of a given logic into the elementary set theory.

[229] Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron and Andrzej Szalas. 2006.
Knowledge Representation Techniques.: a rough set approach.
Book. In series: Studies in Fuzziness and Soft Computing #202. Springer. 342 pages. ISBN: 978-3-540-33518-4, 3-540-33518-8.
DOI: 10.1007/3-540-33519-6.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/hitlist?d=libris&q=9...

The basis for the material in this book centers around a long term research project with autonomous unmanned aerial vehicle systems. One of the main research topics in the project is knowledge representation and reasoning. The focus of the research has been on the development of tractable combinations of approximate and nonmonotonic reasoning systems. The techniques developed are based on intuitions from rough set theory. Efforts have been made to take theory into practice by instantiating research results in the context of traditional relational database or deductive database systems. This book contains a cohesive, self-contained collection of many of the theoretical and applied research results that have been achieved in this project and for the most part pertain to nonmonotonic and approximate reasoning systems developed for an experimental unmanned aerial vehicle system used in the project. This book should be of interest to the theoretician and applied researcher alike and to autonomous system developers and software agent and intelligent system developers.

[228] Full text  Patrick Doherty, Martin Magnusson and Andrzej Szalas. 2006.
Approximate Databases: A support tool for approximate reasoning.
Journal of applied non-classical logics, 16(1-2):87–118. …ditions HermŤs-Lavoisier.
DOI: 10.3166/jancl.16.87-117.
Note: Special issue on implementation of logics

This paper describes an experimental platform for approximate knowledge databases called the Approximate Knowledge Database (AKDB), based on a semantics inspired by rough sets. The implementation is based upon the use of a standard SQL database to store logical facts, augmented with several que