Hide menu

AIICS Publications: Conference and Workshop Publications

Hide abstracts BibTeX entries
2024
[436] Jenny Kunz and Oskar Holmström. 2024.
The Impact of Language Adapters in Cross-Lingual Transfer for NLU.

Modular deep learning has been proposed for the efficient adaption of pre-trained models to new tasks, domains and languages. In particular, combining language adapters with task adapters has shown potential where no supervised data exists for a language. In this paper, we explore the role of language adapters in zero-shot cross-lingual transfer for natural language understanding (NLU) benchmarks. We study the effect of including a target-language adapter in detailed ablation studies with two multilingual models and three multilingual datasets. Our results show that the effect of target-language adapters is highly inconsistent across tasks, languages and models. Retaining the source-language adapter instead often leads to an equivalent, and sometimes to a better, performance. Removing the language adapter after training has only a weak negative effect, indicating that the language adapters do not have a strong impact on the predictions.

[435] Marc Braun and Jenny Kunz. 2024.
A Hypothesis-Driven Framework for the Analysis of Self-Rationalising Models.
In , pages 148–161.

2023
[434] Md Fahim Sikder, Md Ferdous, Shraboni Afroz, Uzzal Podder, Kaniz Fatema, Mohammad Nahid Hossain, Md Tahmid Hasan and Mrinal Kanti Baowaly. 2023.
Explainable Bengali Multiclass News Classification.
In 2023 26th International Conference on Computer and Information Technology (ICCIT). Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9798350359015, 9798350359022.
DOI: 10.1109/ICCIT60459.2023.10441218.

The automatic classification of news articles is crucial in the era of information overflow as it assists readers in accessing relevant information in a timely manner. Even though text classification is not a new area of study, there is potential for advancement concerning the Bengali language. Unlike other languages, Bengali is a complex language, and most of the datasets available online are imbalanced in terms of class label distribution. To increase the performance of classification methods and make them robust to handle imbalanced data, in this work, we propose a model consisting of pre-trained BERT architecture. We use a publicly available dataset of Bengali news articles with nine classes and achieve 92% accuracy. Along with the classification, explaining the model and the result is necessary for the application of trustworthy Artificial Intelligence. From this motivation, we use Integrated Gradient, an explainable AI technique, to explain the outcome of our model. We show which words in a news article affect the model to choose a particular class.

[433] Franziska Babel, Philipp Hock, Sam Thellman and Tom Ziemke. 2023.
Cars As Social Agents (CarSA): A Perspective Shift in Human-Vehicle Interaction.
In PROCEEDINGS OF THE 11TH CONFERENCE ON HUMAN-AGENT INTERACTION, HAI 2023, pages 498–499. ASSOC COMPUTING MACHINERY. ISBN: 9798400708244.
DOI: 10.1145/3623809.3623979.

The rapid advancement of autonomous vehicle (AV) technology has opened up new possibilities and challenges in the domain of human-agent interaction. As AVs become increasingly prevalent on our roads, it is crucial to understand how humans perceive and interact with these intelligent systems. This workshop aims to bring together researchers and practitioners to explore the perception of cars as social agents. We explore the shift in user perception and the implications for interactions between autonomous vehicles, human drivers, and vulnerable road users (pedestrians, cyclists, etc.). Additionally, we investigate the communication of goals and intentions between cars and humans, as well as issues related to mixed agency, stakeholder perspectives, in-vehicle avatars, and human-vehicle power dynamics. The workshop aims to uncover the benefits, risks, and design principles associated with this emerging paradigm.

[432] Adeline Secolo, Paulo Santos, Patrick Doherty and Zoran Sjanic. 2023.
Collaborative Qualitative Environment Mapping.
In AI 2023: Advances in Artificial Intelligence, pages 3–15. In series: Lecture Notes in Computer Science #??. Springer. ISBN: 9789819983902, 9789819983919.
DOI: 10.1007/978-981-99-8391-9_1.
Note: Funding Agencies|CISB, Swedish-Brazilian Research and Innovation Center; Saab AB; Coordenacao de Aperfeicoamento de Pessoal em Nivel Superior - Brasil (CAPES) [001]

This paper explores the use of LH Interval Calculus, a novel qualitative spatial reasoning formalism, to create a human-readable representation of environments observed by UAVs. The system simplifies data from multiple UAVs collaborating on environment mapping. Real UAV-captured data was used for evaluation. In tests involving two UAVs mapping an outdoor area, LH Calculus proved effective in generating a cohesive high-level description of the environment, contingent on consistent input data.

[431] Resmi Ramachandranpillai, Md Fahim Sikder and Fredrik Heintz. 2023.
Fair Latent Deep Generative Models (FLDGMs) for Syntax-Agnostic and Fair Synthetic Data Generation.
In , pages 1938–1945.
DOI: 10.3233/FAIA230484.
Fulltext: https://doi.org/10.3233/FAIA230484

Deep Generative Models (DGMs) for generating synthetic data with properties such as quality, diversity, fidelity, and privacy is an important research topic. Fairness is one particular aspect that has not received the attention it deserves. One difficulty is training DGMs with an in-process fairness objective, which can disturb the global convergence characteristics. To address this, we propose Fair Latent Deep Generative Models (FLDGMs) as enablers for more flexible and stable training of fair DGMs, by first learning a syntax-agnostic, model-agnostic fair latent representation (low dimensional) of the data. This separates the fairness optimization and data generation processes thereby boosting stability and optimization performance. Moreover, data generation in the low dimensional space enhances the accessibility of models by reducing computational demands. We conduct extensive experiments on image and tabular domains using Generative Adversarial Networks (GANs) and Diffusion Models (DMs) and compare them to the state-of-the-art in terms of fairness and utility. Our proposed FLDGMs achieve superior performance in generating high-quality, high-fidelity, and high-diversity fair synthetic data compared to the state-of-the-art fair generative models.

[430] Emanuel Sanchez Aimar, Arvi Jonnarth, Michael Felsberg and Marco Kuhlmann. 2023.
Balanced Product of Calibrated Experts for Long-Tailed Recognition.
In 2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), pages 19967–19977. In series: IEEE Conference on Computer Vision and Pattern Recognition #??. IEEE COMPUTER SOC. ISBN: 9798350301298, 9798350301304.
DOI: 10.1109/CVPR52729.2023.01912.
Note: Funding Agencies|Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; Swedish Research Council [2022-06725]; Knut and Alice Wallenberg Foundation at the National Supercomputer Centre

Many real-world recognition problems are characterized by long-tailed label distributions. These distributions make representation learning highly challenging due to limited generalization over the tail classes. If the test distribution differs from the training distribution, e.g. uniform versus long-tailed, the problem of the distribution shift needs to be addressed. A recent line of work proposes learning multiple diverse experts to tackle this issue. Ensemble diversity is encouraged by various techniques, e.g. by specializing different experts in the head and the tail classes. In this work, we take an analytical approach and extend the notion of logit adjustment to ensembles to form a Balanced Product of Experts (BalPoE). BalPoE combines a family of experts with different test-time target distributions, generalizing several previous approaches. We show how to properly define these distributions and combine the experts in order to achieve unbiased predictions, by proving that the ensemble is Fisher-consistent for minimizing the balanced error. Our theoretical analysis shows that our balanced ensemble requires calibrated experts, which we achieve in practice using mixup. We conduct extensive experiments and our method obtains new state-of-the-art results on three long-tailed datasets: CIFAR-100-LT, ImageNet-LT, and iNaturalist-2018. Our code is available at https://github.com/emasa/BalPoE-CalibratedLT.

[429] Mattias Arvola, Mattias Forsblad (Kristiansson), Mikael Wiberg and Henrik Danielsson. 2023.
Autonomous Vehicles for Children with Mild Intellectual Disability: Perplexity, Curiosity, Surprise, and Confusion.
In Alan Dix, Irene Reppa, Carina Westling, Harry Witchel, Stéphane Safin, Gerrit van der Veer, Joseph MacInnes, Harry Witchel, Raymond Bond, editors, Proceedings of the European Conference on Cognitive Ergonomics 2023: Responsible Technology Community, Culture, and Sustainability, pages 1–8. Association for Computing Machinery (ACM). ISBN: 9798400708756.
DOI: 10.1145/3605655.3605688.
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program -Humanities and Society
Fulltext: https://doi.org/10.1145/3605655.3605688

Self-driving buses will be part of the public transportation system of the future, and they must therefore be accessible to all. The study reported in this paper examines the user experiences of 16 children with mild intellectual disability riding a self-driving bus. The qualitative analysis, performed by iterative affinity diagramming, of interviews, observations, and a co-design session with five of the children, suggests that familiar situations were characterized by contemplation and curiosity, while unfamiliar ones were characterized by surprise or confusion. The temporal structure of past, present, and future situations in the field of attention played a significant role in the children’s experiences. This leads to design considerations for an explainable interior of self-driving buses.

[428] Thorsten Klößner, Jendrik Seipp and Marcel Steinmetz. 2023.
Cartesian Abstractions and Saturated Cost Partitioning in Probabilistic Planning.
In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), pages 1272–1279.
DOI: 10.3233/FAIA230405.

[427] Mauricio Salerno, Raquel Fuentetaja and Jendrik Seipp. 2023.
Eliminating Redundant Actions from Plans using Classical Planning.
In Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning (KR 2023), pages 774–778.
DOI: 10.24963/kr.2023/80.

[426] Paul Höft, David Speck and Jendrik Seipp. 2023.
Sensitivity Analysis for Saturated Post-hoc Optimization in Classical Planning.
In Kobi Gal, Ann Nowé, Grzegorz J. Nalepa, Roy Fairstein, Roxana Rădulescu, editors, Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), pages 1044–1051. In series: Frontiers in Artificial Intelligence and Applications #??. ISBN: 978-1-64368-436-9, 978-1-64368-437-6.
DOI: 10.3233/FAIA230377.
Link: https://ebooks.iospress.nl/doi/10.3233/F...

Cost partitioning is the foundation of today’s strongest heuristics for optimal classical planning. However, computing a cost partitioning for each evaluated state is prohibitively expensive in practice. Thus, existing approaches make an approximation and compute a cost partitioning only for a set of sampled states, and then reuse the resulting heuristics for all other states evaluated during the search. In this paper, we present exact methods for cost partitioning heuristics based on linear programming that fully preserve heuristic accuracy while minimizing computational cost. Specifically, we focus on saturated post-hoc optimization and establish several sufficient conditions for when reusing a cost partitioning computed for one state preserves the estimates for other states, mainly based on a sensitivity analysis of the underlying linear program. Our experiments demonstrate that our theoretical results transfer into practice, and that our exact cost partitioning algorithms are competitive with the strongest approximations currently available, while usually requiring fewer linear program evaluations.

[425] Remo Christen, Salomé Eriksson, Michael Katz, Christian Muise, Alice Petrov, Florian Pommerening, Jendrik Seipp, Silvan Sievers and David Speck. 2023.
PARIS: Planning Algorithms for Reconfiguring Independent Sets.
In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), pages 453–460.
DOI: 10.3233/FAIA230303.
Link: https://ebooks.iospress.nl/doi/10.3233/F...

Combinatorial reconfiguration is the problem of transforming one solution of a combinatorial problem into another, where each transformation may only apply small changes to a solution and may not leave the solution space. An important example is the independent set reconfiguration (ISR) problem, where an independent set of a graph (a subset of its vertices without edges between them) has to be transformed into another by a sequence of transformations that can replace a vertex in the current subset such that the new subset is still an independent set. The 1st Combinatorial Reconfiguration Challenge (CoRe Challenge 2022) was a competition focused on the ISR problem. The PARIS team successfully participated with two solvers that model the ISR problem as a planning task and employ different planning techniques for solving it. In this work, we describe these models and solvers. For a fair comparison to competing ISR approaches, we re-run the entire competition under equal computational conditions. Besides showcasing the success of planning technology, we hope that this work will create a cross-fertilization of the two research fields.

[424] Simon Ståhlberg, Blai Bonet and Hector Geffner. 2023.
Learning General Policies with Policy Gradient Methods.
In Pierre Marquis, Tran Cao Son, Gabriele Kern-Isberner, editors, Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning, pages 647–657. ISBN: 9781956792027.
DOI: 10.24963/kr.2023/63.

While reinforcement learning methods have delivered remarkable results in a number of settings, generalization, i.e., the ability to produce policies that generalize in a reliable and systematic way, has remained a challenge. The problem of generalization has been addressed formally in classical planning where provable correct policies that generalize over all instances of a given domain have been learned using combinatorial methods. The aim of this work is to bring these two research threads together to illuminate the conditions under which (deep) reinforcement learning approaches, and in particular, policy optimization methods, can be used to learn policies that generalize like combinatorial methods do. We draw on lessons learned from previous combinatorial and deep learning approaches, and extend them in a convenient way. From the former, we model policies as state transition classifiers, as (ground) actions are not general and change from instance to instance. From the latter, we use graph neural networks (GNNs) adapted to deal with relational structures for representing value functions over planning states, and in our case, policies. With these ingredients in place, we find that actor-critic methods can be used to learn policies that generalize almost as well as those obtained using combinatorial approaches while avoiding the scalability bottleneck and the use of feature pools. Moreover, the limitations of the DRL methods on the benchmarks considered have little to do with deep learning or reinforcement learning algorithms, and result from the well-understood expressive limitations of GNNs, and the tradeoff between optimality and generalization (general policies cannot be optimal in some domains). Both of these limitations are addressed without changing the basic DRL methods by adding derived predicates and an alternative cost structure to optimize.

[423] Simon Ståhlberg. 2023.
Lifted Successor Generation by Maximum Clique Enumeration.
In Kobi Gal, Ann Nowé, Grzegorz J. Nalepa, Roy Fairstein, Roxana Rădulescu, editors, ECAI 2023. In series: Frontiers in Artificial Intelligence and Applications #??. ISBN: 9781643684369, 9781643684376.

[422] Daniel Gnad, Malte Helmert, Peter Jonsson and Alexander Shleyfman. 2023.
Planning over Integers: Compilations and Undecidability.

[421] Daniel Gnad, Silvan Sievers and Alvaro Torralba. 2023.
Efficient Evaluation of Large Abstractions for Decoupled Search: Merge-and-Shrink and Symbolic Pattern Databases.

[420] Alexander Shleyfman, Daniel Gnad and Peter Jonsson. 2023.
Structurally Restricted Fragments of Numeric Planning ? a Complexity Analysis.

[419] Leif Eriksson and Victor Lagerkvist. 2023.
Improved Algorithms for Allen?s Interval Algebra by Dynamic Programming with Sublinear Partitioning.
In Proceedings of the 32nd International Joint Conference on Artificial Intelligence, pages 1919–1926.
DOI: 10.24963/ijcai.2023/213.

Allen's interval algebra is one of the most well-known calculi in qualitative temporal reasoning with numerous applications in artificial intelligence. Very recently, there has been a surge of improvements in the fine-grained complexity of NP-hard reasoning tasks in this algebra, which has improved the running time from the naive 2^O(n^2) to O*((1.0615n)^n), and even faster algorithms are known for unit intervals and the case when we a bounded number of overlapping intervals. Despite these improvements the best known lower bound is still only 2^o(n) under the exponential-time hypothesis and major improvements in either direction seemingly require fundamental advances in computational complexity. In this paper we propose a novel framework for solving NP-hard qualitative reasoning problems which we refer to as dynamic programming with sublinear partitioning. Using this technique we obtain a major improvement of O*((cn/log(n))^n) for Allen's interval algebra. To demonstrate that the technique is applicable to further problem domains we apply it to a problem in qualitative spatial reasoning, the cardinal direction calculus, and solve it in O*((cn/log(n))^(2n/3)) time. Hence, not only do we significantly advance the state-of-the-art for NP-hard qualitative reasoning problems, but obtain a novel algorithmic technique that is likely applicable to many problems where 2^O(n) time algorithms are unlikely.

[418] Leif Eriksson and Victor Lagerkvist. 2023.
A Fast Algorithm for Consistency Checking Partially Ordered Time.
In Proceedings of the 32nd International Joint Conference on Artificial Intelligence, pages 1911–1918.
DOI: 10.24963/ijcai.2023/212.

Partially ordered models of time occur naturally in applications where agents/processes cannot perfectly communicate with each other, and can be traced back to the seminal work of Lamport. In this paper we consider the problem of deciding if a (likely incomplete) description of a system of events is consistent, the network consistency problem for the point algebra of partially ordered time (POT). While the classical complexity of this problem has been fully settled, comparably little is known of the fine-grained complexity of POT except that it can be solved in O*((0.368n)^n) time by enumerating ordered partitions. We construct a much faster algorithm with a run-time bounded by O*((0.26n)^n), which, e.g., is roughly 1000 times faster than the naive enumeration algorithm in a problem with 20 events. This is achieved by a sophisticated enumeration of structures similar to total orders, which are then greedily expanded toward a solution. While similar ideas have been explored earlier for related problems it turns out that the analysis for POT is non-trivial and requires significant new ideas.

[417] Olle Torstensson and Tjark Weber. 2023.
Hammering Floating-Point Arithmetic.
In Uli Sattler, Martin Suda, editors, FRONTIERS OF COMBINING SYSTEMS, FROCOS 2023, pages 217–235. In series: Lecture Notes in Computer Science #14279. Springer. ISBN: 9783031433689, 9783031433696.
DOI: 10.1007/978-3-031-43369-6_12.
Note: Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

Sledgehammer, a component of the interactive proof assistant Isabelle/HOL, aims to increase proof automation by automatically discharging proof goals with the help of external provers. Among these provers are a group of satisfiability modulo theories (SMT) solvers with support for the SMT-LIB input language. Despite existing formalizations of IEEE floating-point arithmetic in both Isabelle/HOL and SMT-LIB, Sledgehammer employs an abstract translation of floating-point types and constants, depriving the SMT solvers of the opportunity to make use of their dedicated decision procedures for floating-point arithmetic.We show that, by extending Sledgehammer’s translation from the language of Isabelle/HOL into SMT-LIB with an interpretation of floating-point types and constants, floating-point reasoning in SMT solvers can be made available to Isabelle/HOL. Our main contribution is a description and implementation of such an extension. An evaluation of the extended translation shows a significant increase of Sledgehammer’s success rate on proof goals involving floating-point arithmetic.

[416] Johannes K. Fichte, Robert Ganian, Markus Hecher, Friedrich Slivovsky and Sebastian Ordyniak. 2023.
Structure-Aware Lower Bounds and Broadening the Horizon of Tractability for QBF.
In 2023 38TH ANNUAL ACM/IEEE SYMPOSIUM ON LOGIC IN COMPUTER SCIENCE, LICS. In series: IEEE Symposium on Logic in Computer Science #??. IEEE. ISBN: 9798350335873, 9798350335880.
DOI: 10.1109/LICS56636.2023.10175675.
Note: Funding Agencies|Austrian Science Fund (FWF) [J4656, P32830, Y1329]; Society for Research Funding Lower Austria (GFF) [ExzF-0004]; Vienna Science and Technology Fund (WWTF) [ICT19-060, ICT19-065]; ELLIIT - Swedish government

The QSAT problem, which asks to evaluate a quantified Boolean formula (QBF), is of fundamental interest in approximation, counting, decision, and probabilistic complexity and is also considered the prototypical PSPACE-complete problem. As such, it has previously been studied under various structural restrictions (parameters), most notably parameterizations of the primal graph representation of instances. Indeed, it is known that QSAT remains PSPACE-complete even when restricted to instances with constant treewidth of the primal graph, but the problem admits a double-exponential fixed-parameter algorithm parameterized by the vertex cover number (primal graph). However, prior works have left a gap in our understanding of the complexity of QSAT when viewed from the perspective of other natural representations of instances, most notably via incidence graphs. In this paper, we develop structure-aware reductions which allow us to obtain essentially tight lower bounds for highly restricted instances of QSAT, including instances whose incidence graphs have bounded treedepth or feedback vertex number. We complement these lower bounds with novel algorithms for QSAT which establish a nearly-complete picture of the problems complexity under standard graph-theoretic parameterizations. We also show implications for other natural graph representations, and obtain novel upper as well as lower bounds for QSAT under more fine-grained parameterizations of the primal graph.

[415] Sam Thellman, Aksel Holmgren, Max Pettersson and Tom Ziemke. 2023.
Out of Sight, Out of Mind? Investigating People's Assumptions About Object Permanence in Self-Driving Cars.
In Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, pages 602–606. ACM Digital Library. ISBN: 9781450399708.
DOI: 10.1145/3568294.3580156.
Note: Funding: ELLIIT, the Excellence Center at Linkoping-Lund in Information Technology; Swedish Research Council (VR) grant [2022-04602]

Safe and efficient interaction with autonomous road vehicles requires that human road users, including drivers, cyclists, and pedestrians, understand differences between the capabilities and limitations of self-driving vehicles and those of human drivers. In this study, we explore how people judge the ability of self-driving cars versus human drivers to keep track of out-of-sight objects by engaging online study participants in cognitive perspective taking toward a car in an animated traffic scene. The results indicate that people may expect self-driving cars to have similar object permanence capability as human drivers. This finding is important because unmet expectations on autonomous road vehicles can result in undesirable interaction outcomes, such as traffic accidents.

[414] Katarina Sperling, Cormac McGrath, Linnéa Stenliden, Anna Åkerfeldt and Fredrik Heintz. 2023.
Mapping AI Literacy in Teacher Education.
In 2nd International Symposium on Digital Transformation: August 21-23, 2023, Linnaeus University, Växjö.
Link: https://open.lnu.se/index.php/isdt/artic...

Artificial intelligence (AI) is often highlighted as a transformative technology that can“address some of the biggest challenges in education todayâ€(UNESCO, 2019). Introducing data-driven AI in classrooms also raises pedagogical and ethical concerns related to students’, teachers’ and teacher educators’ understanding of how AI works in theory and practice (Holmes, 2022; Sperling et al., 2022). This extended abstract presents initial findings from the first study conducted within the WASP-HS1-funded research project: \"AI Literacy for Swedish Teacher Education - A Participatory Design Approach\". The project aims to establish a scientific foundation for teaching AI literacy in teacher education (TE) programs.

[413] Ehsan Doostmohammadi, Tobias Norlund, Marco Kuhlmann and Richard Johansson. 2023.
Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models.
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 521?529.

Augmenting language models with a retrieval mechanism has been shown to significantly improve their performance while keeping the number of parameters low. Retrieval-augmented models commonly rely on a semantic retrieval mechanism based on the similarity between dense representations of the query chunk and potential neighbors. In this paper, we study the state-of-the-art Retro model and observe that its performance gain is better explained by surface-level similarities, such as token overlap. Inspired by this, we replace the semantic retrieval in Retro with a surface-level method based on BM25, obtaining a significant reduction in perplexity. As full BM25 retrieval can be computationally costly for large datasets, we also apply it in a re-ranking scenario, gaining part of the perplexity reduction with minimal computational overhead.

[412] Oskar Holmström and Ehsan Doostmohammadi. 2023.
Making Instruction Finetuning Accessible to Non-English Languages: A Case Study on Swedish Models.
In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), pages 634–642.
Link: https://aclanthology.org/2023.nodalida-1...

In recent years, instruction finetuning models have received increased attention due to their remarkable zero-shot and generalization capabilities. However, the widespread implementation of these models has been limited to the English language, largely due to the costs and challenges associated with creating instruction datasets. To overcome this, automatic instruction generation has been proposed as a resourceful alternative. We see this as an opportunity for the adoption of instruction finetuning for other languages. In this paper we explore the viability of instruction finetuning for Swedish. We translate a dataset of generated instructions from English to Swedish, using it to finetune both Swedish and non-Swedish models. Results indicate that the use of translated instructions significantly improves the models’ zero-shot performance, even on unseen data, while staying competitive with strong baselines ten times in size. We see this paper is a first step and a proof of concept that instruction finetuning for Swedish is within reach, through resourceful means, and that there exist several directions for further improvements.

[411] Oskar Holmström, Jenny Kunz and Marco Kuhlmann. 2023.
Bridging the Resource Gap: Exploring the Efficacy of English and Multilingual LLMs for Swedish.
In Proceedings of the Second Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2023), pages 92–110.
Link: https://aclanthology.org/2023.resourcefu...

Large language models (LLMs) have substantially improved natural language processing (NLP) performance, but training these models from scratch is resource-intensive and challenging for smaller languages. With this paper, we want to initiate a discussion on the necessity of language-specific pre-training of LLMs. We propose how the “one model-many models†conceptual framework for task transfer can be applied to language transfer and explore this approach by evaluating the performance of non-Swedish monolingual and multilingual models’ performance on tasks in Swedish. Our findings demonstrate that LLMs exposed to limited Swedish during training can be highly capable and transfer competencies from English off-the-shelf, including emergent abilities such as mathematical reasoning, while at the same time showing distinct culturally adapted behaviour. Our results suggest that there are resourceful alternatives to language-specific pre-training when creating useful LLMs for small languages.

[410] Gregor Behnke, David Speck, Michael Katz and Shirin Sohrabi. 2023.
On Partial Satisfaction Planning with Total-Order HTNs.
In Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS 2023), pages 42–51.
Link: https://ojs.aaai.org/index.php/ICAPS/art...

Since its introduction, partial satisfaction planning (PSP), including both oversubscription (OSP) and net-benefit, has received significant attention in the classical planning community. However, hierarchical aspects have been mostly ignored in this context, although several problem domains that form the main motivation for PSP, such as the rover domain, have an inherent hierarchical structure. In this paper, we are taking the necessary steps for facilitating this research direction. First, we formally define hierarchical partial satisfaction planning problems and discuss the usefulness and necessity of this formalism. Second, we present a carefully structured set of benchmarks consisting of OSP and net-benefit problems with hierarchical structure. We describe and analyze the different domains of the benchmark set and the desiderata that are met to provide an interesting and challenging starting point for upcoming research. Third, we introduce various planning techniques that can solve hierarchical OSP problems and investigate their empirical behaviour on our proposed benchmark.

[409] David Speck, Paul Höft, Daniel Gnad and Jendrik Seipp. 2023.
Finding Matrix Multiplication Algorithms with Classical Planning.
In Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS 2023), pages 411–416.
Link: https://ojs.aaai.org/index.php/ICAPS/art...

Matrix multiplication is a fundamental operation of linear algebra, with applications ranging from quantum physics to artificial intelligence. Given its importance, enormous resources have been invested in the search for faster matrix multiplication algorithms. Recently, this search has been cast as a single-player game. By learning how to play this game efficiently, the newly-introduced AlphaTensor reinforcement learning agent is able to discover many new faster algorithms. In this paper, we show that finding matrix multiplication algorithms can also be cast as a classical planning problem. Based on this observation, we introduce a challenging benchmark suite for classical planning and evaluate state-of-the-art planning techniques on it. We analyze the strengths and limitations of different planning approaches in this domain and show that we can use classical planning to find lower bounds and concrete algorithms for matrix multiplication.

[408] Ella Olsson, Mikael Nilsson, Kristoffer Bergman, Daniel de Leng, Stefan Carlén, Emil Karlsson and Bo Granbom. 2023.
Urdarbrunnen: Towards an AI-enabled mission system for Combat Search and Rescue operations.
In HÃ¥kan Grahn, Anton Borg, Martin Boldt, editors, Proceedings of the 35th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS 2023), pages 38–45. In series: Linköping Electronic Conference Proceedings #199. Linköping University Electronic Press. ISBN: 978-91-8075-274-9.
DOI: 10.3384/ecp199004.
Fulltext: https://doi.org/10.3384/ecp199004

The Urdarbrunnen project is a Saab-led exploratory initiative that aims to develop an operator-assisted AI-enabled mission system for basic autonomous functions. In its first iteration, presented in this project paper, the system is designed to be capable of performing the search task of a combat search and rescue mission in a complex and dynamic environment, while providing basic human machine interaction support for remote operators. The system enables a team of agents to cooperatively plan and execute a search mission while also interfacing with the WARA-PS core system that allows human operators and other agents to monitor activities and interact with each other. The aim of the project is to develop the system iteratively, with each iteration incorporating feedback from simulations and real-world experiments. In future work, the capability of the system will be extended to incorporate additional tasks for other scenarios, making it a promising starting point for the integration of autonomous capabilities in a future air force.

[407] Dominik Drexler, Jendrik Seipp and Hector Geffner. 2023.
Learning Hierarchical Policies by Iteratively Reducing the Width of Sketch Rules.
In 20th International Conference on Principles of Knowledge Representation and Reasoning, Rhodes, Greece, September 2-8, 2023.

Hierarchical policies are a key ingredient of intelligent behavior, expressing the different levels of abstraction involved in the solution of a problem. Learning hierarchical policies, however, remains a challenge, as no general learning principles have been identified for this purpose, despite the broad interest and vast literature in both model-free reinforcement learning and model-based planning. In this work, we introduce a principled method for learning hierarchical policies over classical planning domains, with no supervision from small instances. The method is based on learning to decompose problems into subproblems so that the subproblems have a lower complexity as measured by their width. Problems and subproblems are captured by means of sketch rules, and the scheme for reducing the width of sketch rules is applied iteratively until the final sketch rules have zero width and encode a general policy. We evaluate the learning method on a number of classical planning domains, analyze the resulting hierarchical policies, and prove their properties. We also show that learning hierarchical policies by learning and refining sketches iteratively is often more efficient than learning flat general policies in one shot.

[406] Tobias Norlund, Ehsan Doostmohammadi, Richard Johansson and Marco Kuhlmann. 2023.
On the Generalization Ability of Retrieval-Enhanced Transformers.
In Findings of the Association for Computational Linguistics, pages 1485–1493.

[405] Mattias Tiger, David Bergström, Simon Wijk Stranius, Evelina Holmgren, Daniel de Leng and Fredrik Heintz. 2023.
On-Demand Multi-Agent Basket Picking for Shopping Stores.
In 2023 IEEE International Conference on Robotics and Automation (ICRA), pages 5793–5799. IEEE. ISBN: 9798350323658, 9798350323665.
DOI: 10.1109/ICRA48891.2023.10160398.
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); Knut and Alice Wallenberg Foundation [KAW 2019.0350]; TAILOR Project - EU Horizon 2020 research and innovation programme [952215]
fulltext:postprint: https://liu.diva-portal.org/smash/get/di...

Imagine placing an online order on your way to the grocery store, then being able to pick the collected basket upon arrival or shortly after. Likewise, imagine placing any online retail order, made ready for pickup in minutes instead of days. In order to realize such a low-latency automatic warehouse logistics system, solvers must be made to be basketaware. That is, it is more important that the full order (the basket) is picked timely and fast, than that any single item in the order is picked quickly. Current state-of-the-art methods are not basket-aware. Nor are they optimized for a positive customer experience, that is; to prioritize customers based on queue place and the difficulty associated with picking their order. An example of the latter is that it is preferable to prioritize a customer ordering a pack of diapers over a customer shopping a larger order, but only as long as the second customer has not already been waiting for too long. In this work we formalize the problem outlined, propose a new method that significantly outperforms the state-of-the-art, and present a new realistic simulated benchmark. The proposed method is demonstrated to work in an on-line and real-time setting, and to solve the on-demand multi-agent basket picking problem for automated shopping stores under realistic conditions.

[404] Johan Källström and Fredrik Heintz. 2023.
Model-Based Multi-Objective Reinforcement Learning with Dynamic Utility Functions.
In Proceedings of the Adaptive and Learning Agents Workshop (ALA) at AAMAS 2023, pages 1–9.
Workshop Website: https://alaworkshop2023.github.io/
Paper Link: https://alaworkshop2023.github.io/papers...

Many real-world problems require a trade-off between multiple conflicting objectives. Decision-makers’ preferences over solutions to such problems are determined by their utility functions, which convert multi-objective values to scalars. In some settings, utility functions change over time, and the goal is to find methods that can efficiently adapt an agent’s policy to changes in utility. Previous work on learning with dynamic utility functions has focused on model-free methods, which often suffer from poor sample efficiency. In this work, we instead propose a model-based actor-critic, which explores with diverse utility functions through imagined rollouts within a learned world model between interactions with the real environment. An experimental evaluation shows that by learning a model of the environment the performance of the agent can be improved compared to model-free algorithms.

[403] Conor F. Hayes, Roxana R?dulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel Ramos, Marcello Restelli, Peter Vamplew and Diederik M. Roijers. 2023.
A Brief Guide to Multi-Objective Reinforcement Learning and Planning.
In A. Ricci, W. Yeoh, N. Agmon, B. An, editors, Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 1988–1990. ISBN: 978-1-4503-9432-1.
Proceedings: https://www.ifaamas.org/Proceedings/aama...

Real-world sequential decision-making tasks are usually complex, and require trade-offs between multiple–often conflicting–objectives. However, the majority of research in reinforcement learning (RL) and decision-theoretic planning assumes a single objective, or that multiple objectives can be handled via a predefined weighted sum over the objectives. Such approaches may oversimplify the underlying problem, and produce suboptimal results. This extended abstract outlines the limitations of using a semi-blind iterative process to solve multi-objective decision making problems. Our extended paper [4], serves as a guide for the application of explicitly multi-objective methods to difficult problems.

[402] Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel Ramos, Roxana R?dulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J.K. Libin, Richard Dazeley and Cameron Foale. 2023.
Scalar Reward is Not Enough.
In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 839–841. ISBN: 978-1-4503-9432-1.
Proceedings: https://www.ifaamas.org/Proceedings/aama...

Silver et al.[14] posit that scalar reward maximisation is sufficient to underpin all intelligence and provides a suitable basis for artificial general intelligence (AGI). This extended abstract summarises the counter-argument from our JAAMAS paper [19].

[401] Johan Källström and Fredrik Heintz. 2023.
Model-Based Actor-Critic for Multi-Objective Reinforcement Learning with Dynamic Utility Functions.
In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 2818–2820. ISBN: 978-1-4503-9432-1.
Proceedings: https://www.ifaamas.org/Proceedings/aama...

Many real-world problems require a trade-off between multiple conflicting objectives. Decision-makers’ preferences over solutions to such problems are determined by their utility functions, which convert multi-objective values to scalars. In some settings, utility functions change over time, and the goal is to find methods that can efficiently adapt an agent’s policy to changes in utility. Previous work on learning with dynamic utility functions has focused on model-free methods, which often suffer from poor sample efficiency. In this work, we instead propose a model-based actor-critic, which explores with diverse utility functions through imagined rollouts within a learned world model between interactions with the real environment. An experimental evaluation on Minecart, a well-known benchmark for multi-objective reinforcement learning, shows that by learning a model of the environment the quality of the agent’s policy is improved compared to model-free algorithms.

[400] Linda Mannila. 2023.
Viewing the Finnish national curriculum through AI glasses: participatory design for integrating AI in grades 1-9.
In .

The research described in this position paper aims at addressing the emerging need for scientifically grounded guidance on how tointroduce AI in K-12 education in Finland. Although there are currently no explicit requirements to teach AI in the Finnish curriculum, digital competence, including programming, is to be integrated across the curriculum. We propose that programming can be used as a gateway for introducing AI, since both programming and AI can be viewed from a technological (using, modifying, creating) and a societal perspective (questions related to ethics, security and privacy). Also, connecting programming education to a given context, such as AI, can help organize the content into a meaningful whole and anchor it in students’ reality by considering current phenomena. The proposed research builds on a design-based methdology including close collaboration with teachers, addressing questions related to curriculum design and evaluation as well as teacher training and professional development.

[399] Linda Mannila and Mia Skog. 2023.
"Look at our smart shoe" - a scalable online concept for introducing design as part of computational thinking in grades 1-6.
In 22ND ANNUAL ACM INTERACTION DESIGN AND CHILDREN CONFERENCE, IDC 2023: Rediscovering Childhood, pages 222–232. ASSOC COMPUTING MACHINERY. ISBN: 9798400701313.
DOI: 10.1145/3585088.3589377.
Note: Funding: Marcus and Amalia Wallenberg Foundation

While programming is a process covering many stages, many of the tasks K-12 students meet at school are small with little need for, e.g., analysis or design. These earlier phases are, however, important to let children meet open-ended problems, brainstorm solutions and ideate their own creative designs. In this paper, we present a model for an online, scalable and scaffolded design workshop for covering such aspects at K-12 level. Through a case study with 1200 students and 60 teachers on IoT and smart things, we describe the workshop and the resulting designs. While the students managed to design their own artifacts, more time had been needed for covering ethical aspects related to technology design. The results suggest creating separate workshops for different grade levels, and also for design and ethical aspects respectively. Moreover, additional resources could support teachers in continuing the discussion with the students after the workshop.

[398] Sam Thellman, Erik Marsja, Anna Anund and Tom Ziemke. 2023.
Will It Yield: Expectations on Automated Shuttle Bus Interactions With Pedestrians and Bicyclists.
In HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, pages 292–296. Association for Computing Machinery (ACM). ISBN: 9781450399708.
DOI: 10.1145/3568294.3580091.
Note: Funding: ELLIIT, the Excellence Center at Linkoping-Lund in Information Technology; Swedish Research Council (VR) [2022-04602]
Fulltext: https://doi.org/10.1145/3568294.3580091

Autonomous vehicles that operate on public roads need to be predictable to others, including vulnerable road users. In this study, we asked participants to take the perspective of videotaped pedestrians and cyclists crossing paths with an automated shuttle bus, and to (1) judge whether the bus would stop safely in front of them and (2) report whether the bus's actual stopping behavior accorded with their expectations. The results show that participants expected the bus to brake safely in approximately two thirds of the human-vehicle interactions, more so to pedestrians than cyclists, and that they tended to underestimate rather than overestimate the bus's capability to yield in ways that they considered as safe. These findings have implications for the design and implementation of automated shuttle bus services.

[397] Filip Strömbäck, Linda Mannila and Mariam Kamkar. 2023.
Using Model-Checking and Peer-Grading to Provide Automated Feedback to Concurrency Exercises in Progvis.
In ACE '23: Proceedings of the 25th Australasian Computing Education Conference, pages 11–20. In series: ACE ?23 #??. Association for Computing Machinery. ISBN: 9781450399418.
DOI: 10.1145/3576123.3576125.
Fulltext: https://doi.org/10.1145/3576123.3576125
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Previous research has shown that even though many students are aware of overarching problems with concurrency, they are less successful in addressing any issues they have found. This implies that the students have not yet developed a mental model that describes the behavior of concurrent systems with enough accuracy. One way to help students explore the non-determinism of concurrent systems and thereby develop their mental model is through the use of visualization tools. One example of such a tool is Progvis, which provides students with a detailed visualization of the program state, and allows students to single-step individual threads to explore the program’s behavior in a concurrent environment. One problem with this type of tools is that they are not able to provide feedback on whether or not a proposed solution is correct, which limits their percieved usefulness. To increase the percieved usefulness of Progvis, we extended it with a system that utilizes model-checking and peer-grading to provide automated feedback to students. Our hopes were that this would encourage students to further use Progvis to practice concurrent programming. The system was used during two years in a course on concurrency and operating systems. This made it possible to utilize the experiences from the first year to further improve the system for the second year. Overall, the students expressed that they found our additions helpful. Additionally, we observed a slight increase in usage in the second year compared to the first year, which suggests that the improvements in the second year increased students’ motivation to some extent.

2022
[396] Leif Eriksson and Victor Lagerkvist. 2022.
A Multivariate Complexity Analysis of Qualitative Reasoning Problems.
In Proceedings of the 31st International Joint Conference on Artificial Intelligence, pages 1804–1810.
DOI: 10.24963/ijcai.2022/251.

Qualitative reasoning is an important subfield of artificial intelligence where one describes relationships with qualitative, rather than numerical, relations. Many such reasoning tasks, e.g., Allen's interval algebra, can be solved in 2^O(n*log n) time, but single-exponential running times 2^O(n) are currently far out of reach. In this paper we consider single-exponential algorithms via a multivariate analysis consisting of a fine-grained parameter n (e.g., the number of variables) and a coarse-grained parameter k expected to be relatively small. We introduce the classes FPE and XE of problems solvable in f(k)*2^O(n), respectively f(k)^n, time, and prove several fundamental properties of these classes. We proceed by studying temporal reasoning problems and (1) show that the partially ordered time problem of effective width k is solvable in 16^{kn} time and is thus included in XE, and (2) that the network consistency problem for Allen's interval algebra with no interval overlapping with more than k others is solvable in (2nk)^{2k}*2^n time and is included in FPE. Our multivariate approach is in no way limited to these to specific problems and may be a generally useful approach for obtaining single-exponential algorithms.

[395] Ehsan Doostmohammadi and Marco Kuhlmann. 2022.
On the Effects of Video Grounding on Language Models.
In Proceedings of the First Workshop on Performance and Interpretability Evaluations of Multimodal, Multipurpose, Massive-Scale Models.

Transformer-based models trained on text and vision modalities try to improve the performance on multimodal downstream tasks or tackle the problem Transformer-based models trained on text and vision modalities try to improve the performance on multimodal downstream tasks or tackle the problem of lack of grounding, e.g., addressing issues like models’ insufficient commonsense knowledge. While it is more straightforward to evaluate the effects of such models on multimodal tasks, such as visual question answering or image captioning, it is not as well-understood how these tasks affect the model itself, and its internal linguistic representations. In this work, we experiment with language models grounded in videos and measure the models’ performance on predicting masked words chosen based on their imageability. The results show that the smaller model benefits from video grounding in predicting highly imageable words, while the results for the larger model seem harder to interpret.of lack of grounding, e.g., addressing issues like models’ insufficient commonsense knowledge. While it is more straightforward to evaluate the effects of such models on multimodal tasks, such as visual question answering or image captioning, it is not as well-understood how these tasks affect the model itself, and its internal linguistic representations. In this work, we experiment with language models grounded in videos and measure the models’ performance on predicting masked words chosen based on their imageability. The results show that the smaller model benefits from video grounding in predicting highly imageable words, while the results for the larger model seem harder to interpret.

[394] Jenny Kunz, Martin Jirénius, Oskar Holmström and Marco Kuhlmann. 2022.
Human Ratings Do Not Reflect Downstream Utility: A Study of Free-Text Explanations for Model Predictions.
In Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, pages 164–177.
Link: https://aclanthology.org/2022.blackboxnl...

Models able to generate free-text rationales that explain their output have been proposed as an important step towards interpretable NLP for “reasoning†tasks such as natural language inference and commonsense question answering. However, the relative merits of different architectures and types of rationales are not well understood and hard to measure. In this paper, we contribute two insights to this line of research: First, we find that models trained on gold explanations learn to rely on these but, in the case of the more challenging question answering data set we use, fail when given generated explanations at test time. However, additional fine-tuning on generated explanations teaches the model to distinguish between reliable and unreliable information in explanations. Second, we compare explanations by a generation-only model to those generated by a self-rationalizing model and find that, while the former score higher in terms of validity, factual correctness, and similarity to gold explanations, they are not more useful for downstream classification. We observe that the self-rationalizing model is prone to hallucination, which is punished by most metrics but may add useful context for the classification step.

[393] Susanne Kjällander, Anna Åkerfeldt, Linda Mannila and Fredrik Heintz. 2022.
Signs of learning in middle school computing education.
In . In series: 2022 IEEE Frontiers in Education Conference (FIE) #??. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781665462440, 9781665462457.
DOI: 10.1109/FIE56618.2022.9962658.

Programming has been part of Swedish elementary school curriculum for six years and the aim of this full paper is to find out how teachers can design programming activities so that students engage and learn. A mix-methods research project with a social semiotic, multimodal theoretical framework – Designs for learning – is used to investigate teaching and learning in a class during three years. The results in this small-scale study indicate that collaboration is a successful didactic design for programming lessons in school. Computational thinking is prevalent and both digital skills (such as coding) and digital competencies (such as understanding the impact of technology in society) are practiced and met in programming lessons merging Science, Technology, Engineering, Arts, and Mathematics.

[392] Anna Åkerfeldt, Susanne Kjällander, Linda Mannila and Fredrik Heintz. 2022.
Exploring programming didactics in primary school - a gender perspective.
In 2022 IEEE Frontiers in Education Conference (FIE). In series: Frontiers in Education (FIE) Conference #??. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781665462440, 9781665462457.
DOI: 10.1109/FIE56618.2022.9962386.

This Research Full Paper explore inclusion in programming in primary school. Education plays a crucial role in engaging a diverse group of students with different social backgrounds and interests. Therefore, this study aims to shed light upon inclusion in programming in primary school, focusing on gender to increase the knowledge regarding inclusion in programming didactics. The following research questions have guided the study: How are programming activities designed in primary school? How do pupils approach the programming tasks given? Can any gender differences be observed, and what are the consequences for the teaching practice? The theoretical framework used to analyse the empirical material is at the intersection between multimodal social semiotics [1] and a design-oriented perspective [2]. The empirical material consists of classroom video observations. Programming lessons in grades 4-8 have been observed and videos was recorded during 2019-2020. The pupils have worked on eight different programming tasks during the lessons. Analysis of these programming activities (tasks, instructions and resources used) focusing on gender has been made. Findings show two aspects 1) interest and position and 2) representations of knowledge. Regarding interest and position, the study of programming activities shows both similarities and differences between girls’ and boys’ approach to the task. Similarities are shown regarding the learning activities. No differences in coding strategies or creativity are observed if the task has an open design. The differences are shown in the guided tasks, where boys tend to engage in the tasks from their interests rather than following instructions and girls tend to follow the instructions given by the teacher. From a gender perspective, the boys might find programming more creative and fun, and the girls might feel less engaged as their interest falls into the background. Secondly, knowledge representations might affect who is seen as an expert within the CS field. For example, in grades 4 and 5, a male voice was represented in the video clips and a guest teacher used when presenting programming activities. The resources used in the lessons can be seen as representations of knowledge. In this case, they are always connected to a social and cultural domain [3], an environment foremost represented by males in this case.

[391] Linda Mannila, Anna Åkerfeldt, Susanne Kjällander and Fredrik Heintz. 2022.
Exploring Gender Differences in Primary School Programming.
In 2022 IEEE Frontiers in Education Conference (FIE). In series: Frontiers in Education (FIE) Conference #??. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781665462440, 9781665462457.
DOI: 10.1109/FIE56618.2022.9962482.

As a result of the increased digitalisation, many countries have introduced programming in their primary education curricula. One main objective is to give all children equal opportunities to develop the skills needed to be an active participant and producer in a digitalized society. This also addresses another important objective, that of increased diversity and broadened participation. Despite technology being a natural part in our everyday lives, stereotypical views of programming as a primarily male activity still exist. In this paper, we explore girls’ and boys’ experiences of programming at school and in their spare time. The study is situated in primary school classrooms in Sweden, where programming was introduced in a cross-curricular manner as part of digital competence in 2018. While most students reported having some programming experience, it was quite limited. The results show that, compared to the girls, boys in grades 4-9 are somewhat more positive towards programming and get more programming experience both at school and in their spare time. Similarly, boys rated their self-perceived programming skills higher than the girls. In grades 1-3, no gender disparity was found in students’ attitudes, experiences or skills. However, the gender differences in grades 4-9 were not reflected to an equally high extent in the students’ programming skills, as girls and boys did equally well on many skills related tasks. The analysis highlights the importance of well planned, motivating and relevant tasks in order to provide positive experiences of programming in the classroom.

[390] Hector Geffner. 2022.
Target Languages (vs. Inductive Biases) for Learning to Act and Plan.
In THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, pages 12326–12333. In series: AAAI Conference on Artificial Intelligence #??. ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. ISBN: 9781577358763.
DOI: 10.1609/aaai.v36i11.21497.
Note: Funding Agencies|ERC Advanced Grant [885107]; EU Horizon 2020 project TAILOR [952215]; Knut and AliceWallenberg (KAW) Foundation

Recent breakthroughs in AI have shown the remarkable power of deep learning and deep reinforcement learning. These developments, however, have been tied to specific tasks, and progress in out-of-distribution generalization has been limited. While it is assumed that these limitations can be overcome by incorporating suitable inductive biases, the notion of inductive biases itself is often left vague and does not provide meaningful guidance. In the paper, I articulate a different learning approach where representations do not emerge from biases in a neural architecture but are learned over a given target language with a known semantics. The basic ideas are implicit in mainstream AI where representations have been encoded in languages ranging from fragments of first-order logic to probabilistic structural causal models. The challenge is to learn from data, the representations that have traditionally been crafted by hand. Generalization is then a result of the semantics of the language. The goals of this paper are to make these ideas explicit, to place them in a broader context where the design of the target language is crucial, and to illustrate them in the context of learning to act and plan. For this, after a general discussion, I consider learning representations of actions, general policies, and subgoals (\"intrinsic rewards\"). In these cases, learning is formulated as a combinatorial problem but nothing prevents the use of deep learning techniques instead. Indeed, learning representations over languages with a known semantics provides an account of what is to be learned, while learning representations with neural nets provides a complementary account of how representations can be learned. The challenge and the opportunity is to bring the two together.

[389] Jenny Kunz and Marco Kuhlmann. 2022.
Where Does Linguistic Information Emerge in Neural Language Models?: Measuring Gains and Contributions across Layers.
In Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na, editors, Proceedings of the 29th International Conference on Computational Linguistics, pages 4664–4676.

Probing studies have extensively explored where in neural language models linguistic information is located. The standard approach to interpreting the results of a probing classifier is to focus on the layers whose representations give the highest performance on the probing task. We propose an alternative method that asks where the task-relevant information emerges in the model. Our framework consists of a family of metrics that explicitly model local information gain relative to the previous layer and each layer’s contribution to the model’s overall performance. We apply the new metrics to two pairs of syntactic probing tasks with different degrees of complexity and find that the metrics confirm the expected ordering only for one of the pairs. Our local metrics show a massive dominance of the first layers, indicating that the features that contribute the most to our probing tasks are not as high-level as global metrics suggest.

[388] Patrick Ferber, Liat Cohen, Jendrik Seipp and Thomas Keller. 2022.
Learning and Exploiting Progress States in Greedy Best-First Search.
In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), pages 4740–4746.
DOI: 10.24963/ijcai.2022/657.
Fulltext: https://doi.org/10.24963/ijcai.2022/657

Previous work introduced the concept of progress states. After expanding a progress state, a greedy best-first search (GBFS) will only expand states with lower heuristic values. Current methods can identify progress states only for a single task and only after a solution for the task has been found. We introduce a novel approach that learns a description logic formula characterizing all progress states in a classical planning domain. Using the learned formulas in a GBFS to break ties in favor of progress states often significantly reduces the search effort.

[387] Augusto B. Corrêa and Jendrik Seipp. 2022.
Best-First Width Search for Lifted Classical Planning.
In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pages 11–15.
DOI: 10.1609/icaps.v32i1.19780.
Fulltext: https://doi.org/10.1609/icaps.v32i1.1978...

Lifted planners are useful to solve tasks that are too hard to ground. Still, computing informative lifted heuristics is difficult: directly adapting ground heuristics to the lifted setting is often too expensive, and extracting heuristics from the lifted representation can be uninformative. A natural alternative for lifted planners is to use width-based search. These algorithms are among the strongest for ground planning, even the variants that do not access the action model. In this work, we adapt best-first width search to the lifted setting and show that this yields state-of-the-art performance for hard-to-ground planning tasks.

[386] Patrick Ferber and Jendrik Seipp. 2022.
Explainable Planner Selection for Classical Planning.
In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), pages 9741–9749. In series: AAAI Conference on Artificial Intelligence #??. AAAI Press.
DOI: 10.1609/aaai.v36i9.21209.
Note: Funding: Swiss National Science Foundation (SNSF) as part of the project "Certified Correctness and Guaranteed Performance for Domain-Independent Planning" (CCGP-Plan); TAILOR - EU [952215]; Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation; DFG [389792660, TRR 248]
Fulltext: https://doi.org/10.1609/aaai.v36i9.21209

Since no classical planner consistently outperforms all others, it is important to select a planner that works well for a given classical planning task. The two strongest approaches for planner selection use image and graph convolutional neural networks. They have the drawback that the learned models are complicated and uninterpretable. To obtain explainable models, we identify a small set of simple task features and show that elementary and interpretable machine learning techniques can use these features to solve roughly as many tasks as the complex approaches based on neural networks.

[385] Filip Strömbäck, Linda Mannila and Mariam Kamkar. 2022.
A Weak Memory Model in Progvis: Verification and Improved Accuracy of Visualizations of Concurrent Programs to Aid Student Learning.
In Ilkka Jormanainen, Andrew Petersen, editors, Koli Calling '22: Proceedings of the 22nd Koli Calling International Conference on Computing Education Research. ACM Publications. ISBN: 9781450396165.
DOI: 10.1145/3564721.3565947.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

Previous research has shown that many students struggle with solving small concurrency problems after their first course on concurrency. A possible reason for this is that students do not have a suitable mental model of the semantics of the underlying programming language, and are therefore not able to properly reason about the program’s behavior. One way to help students learn concurrency and improve their mental model is through the use of visualization tools. Progvis is one such visualization tool that is not only aimed at concepts related to concurrency, but also provides an accurate visualization of more fundamental concepts to illustrate how they interact with concurrency. In previous work, the authors of Progvis performed a small-scale evaluation of the tool, and highlighted some areas of improvement. In this paper, we address these shortcomings by improving the memory model visualized by Progvis and implementing a model checker. We also evaluate Progvis on a larger scale by incorporating it into a course on concurrency and operating systems, which allows assessing whether using Progvis aids students in learning concurrency. The results indicate that Progvis (with our improvements) is successful in helping students realize how concurrency interacts with more fundamental concepts, and that students find it useful in helping them understand the content of the concurrency assignments.

[384] Kilian Hu and David Speck. 2022.
On Bidirectional Heuristic Search in Classical Planning: An Analysis of BAE*.
In Proceedings of the 15th Annual Symposium on Combinatorial Search (SoCS 2022), pages 91–99.
Link: https://ojs.aaai.org/index.php/SOCS/arti...

Heuristic search is a successful approach to cost-optimal planning. Bidirectional heuristic search algorithms have been around for a long time, but only recent advances have led to algorithms like BAE* that have the potential to outperform unidirectional heuristic search algorithms like A* in practice. In this work, we analyze BAE* for classical planning and the challenges associated with the underlying assumption of an explicit state representation. We show that it is crucial to use mutexes and reachability analysis to reduce the potentially exponential number of goal states, which makes it possible to create an explicit representation of a reversed planning task that can be used for the backward search of BAE*. Our empirical evaluation shows that BAE* solves more instances than A* in multiple domains with significantly fewer node expansions, demonstrating the usefulness of BAE* in planning.

[383] Julian von Tschammer, Robert Mattmüller and David Speck. 2022.
Loopless Top-K Planning.
In Proceedings of the 32nd International Conference on Automated Planning and Scheduling (ICAPS 2022), pages 380–384.
Link: https://ojs.aaai.org/index.php/ICAPS/art...

In top-k planning, the objective is to determine a set of k cheapest plans that provide several good alternatives to choose from. Such a solution set often contains plans that visit at least one state more than once. Depending on the application, plans with such loops are of little importance because they are dominated by a loopless representative and can prevent more meaningful plans from being found.In this paper, we motivate and introduce loopless top-k planning. We show how to enhance the state-of-the-art symbolic top-k planner, symK, to obtain an efficient, sound and complete algorithm for loopless top-k planning. An empirical evaluation shows that our proposed approach has a higher k-coverage than a generate-and-test approach that uses an ordinary top-k planner, which we show to be incomplete in the presence of zero-cost loops.

[382] Barbara Dunin-Keplicz and Andrzej Szalas. 2022.
Modeling and Shadowing Paraconsistent BDI Agents.
In 10th International Workshop on Engineering Multi-Agent Systems.
Link: https://emas.in.tu-clausthal.de/2022/pap...

For over three decades researchers have been studying the BDI modelof agency. Many robust multiagent systems have been developed, and a numberof BDI logics have been studied. Following this intensive development phase, theimportance of integrating BDI models with inconsistency handling and revisiontheory have been emphasized. There is also a demand for a tighter connectionbetween BDI-based implementations and BDI logics. In this paper, we addressthese postulates by introducing a novel, paraconsistent logical BDI model close toimplementation, with building blocks that can be represented as SQL/rule-baseddatabases. Importantly, tractability is achieved by reasoning as querying. Thisstands in a sharp contrast to the high complexity of BDI logics. We also extendbelief shadowing, a shallow and lightweight alternative to deep and computation-ally demanding belief revision, to encompass agents’ motivational attitudes.

[381] Andrzej Szalas. 2022.
Inheriting and Fusing Beliefs of Logically Heterogeneous Objects.
In Matteo Cristani, Carlos Toro, Cecilia Zanni-Merk, Robert J. Howlett, Lakhmi C. Jain, editors, 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, pages 299–308. In series: Procedia Computer Science #??. Elsevier.
DOI: 10.1016/j.procs.2022.09.063.
Fulltext: https://doi.org/10.1016/j.procs.2022.09....

Inheritance has intensively been studied in both object-oriented programming (Oop) and knowledge representation and reasoning (KRR). On the other hand, the approaches to multiple inheritance and related method resolution, developed in both domains, remain separated. The primary goal of this paper is to demonstrate how these approaches may be integrated using inheritance expressions. In particular, we examine inheritance as a belief bases management machinery designed to operate in dynamically changing environments where objects are embedded and act. We focus on objects that are belief bases containers, potentially participating in complex distributed reasoning scenarios. We show that inheritance expressions, inspired both by Oop and KRR, provide a simple yet flexible and powerful means for expressing inheritance and related belief/knowledge fusion.

[380] Andrzej Szalas. 2022.
Querying and Reasoning in Paraconsistent Rule-Object Languages with Inheritance Expressions.
In Nguyen, N.T., Manolopoulos, Y., Chbeir, R., Kozierkiewicz, A., TrawiÅ„ski, B., editors, ICCCI 2022: Computational Collective Intelligence, pages 396–409. In series: Lecture Notes in Computer Science #13501. Springer. ISBN: 9783031160141, 9783031160134.
DOI: 10.1007/978-3-031-16014-1_32.
Note: Funding: Polish National Science Centre [2017/27/B/ST6/02018]

Inheritance has intensively been investigated during the past decades in object-oriented programming and knowledge representation and reasoning areas. In the paper we focus on recently introduced inheritance expressions that allow one to represent dynamic concept hierarchies as well as fuse and disambiguate beliefs acquired by the objects involved. We focus on querying and reasoning about inheritance expressions using a four-valued paraconsistent formalism that has been developed over the last ten years. In particular, we show that querying inheritance expressions and formulas can be efficiently implemented. In addition, we provide tableaux for general reasoning purposes. Complexity of the investigated tools is also analyzed.

[379] David Speck and Jendrik Seipp. 2022.
New Refinement Strategies for Cartesian Abstractions.
In Proceedings of the 32nd International Conference on Automated Planning and Scheduling (ICAPS 2022), pages 348–352.
Link: https://ojs.aaai.org/index.php/ICAPS/art...

Cartesian counterexample-guided abstraction refinement (CEGAR) yields strong heuristics for optimal classical planning. CEGAR repeatedly finds counterexamples, i.e., abstract plans that fail for the concrete task. Although there are usually many such abstract plans to choose from, the refinement strategy from previous work is to choose an arbitrary optimal one. In this work, we show that an informed refinement strategy is critical in theory and practice. We demonstrate that it is possible to execute all optimal abstract plans in the concrete task simultaneously, and present methods to minimize the time and number of refinement steps until we find a concrete solution. The resulting algorithm solves more tasks than the previous state of the art for Cartesian CEGAR, both during refinement and when used as a heuristic in an A* search.

[378] Daniel Engelsons, Mattias Tiger and Fredrik Heintz. 2022.
Coverage Path Planning in Large-scale Multi-floor Urban Environments with Applications to Autonomous Road Sweeping.
In 2022 International Conference on Robotics and Automation (ICRA), pages 3328–3334. Institute of Electrical and Electronics Engineers (IEEE). ISBN: 9781728196817, 9781728196824.
DOI: 10.1109/ICRA46639.2022.9811941.
Note: Funding: 10.13039/501100004063-Knut and Alice Wallenberg Foundation (Grant Number: KAW 2019.0350)
fulltext:postprint: https://liu.diva-portal.org/smash/get/di...

Coverage Path Planning is the work horse of contemporary service task automation, powering autonomous floor cleaning robots and lawn mowers in households and office sites. While steady progress has been made on indoor cleaning and outdoor mowing, these environments are small and with simple geometry compared to general urban environments such as city parking garages, highway bridges or city crossings. To pave the way for autonomous road sweeping robots to operate in such difficult and complex environments, a benchmark suite with three large-scale 3D environments representative of this task is presented. On this benchmark we evaluate a new Coverage Path Planning method in comparison with previous well performing algorithms, and demonstrate state-of-the-art performance of the proposed method. Part of the success, for all evaluated algorithms, is the usage of automated domain adaptation by in-the-loop parameter optimization using Bayesian Optimization. Apart from improving the performance, tedious and bias-prone manual tuning is made obsolete, which makes the evaluation more robust and the results even stronger.

[377] Simon Ståhlberg, Blai Bonet and Hector Geffner. 2022.
Learning Generalized Policies without Supervision Using GNNs.
In Proceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning: Special Session on KR and Machine Learning, pages 474–483. In series: Proceedings of the Conference on Principles of Knowledge Representation and Reasoning (KR) #??. IJACAI Organization. ISBN: 978-1-956792-01-0.
DOI: 10.24963/kr.2022/49.

We consider the problem of learning generalized policies forclassical planning domains using graph neural networks fromsmall instances represented in lifted STRIPS. The problemhas been considered before but the proposed neural architec-tures are complex and the results are often mixed. In thiswork, we use a simple and general GNN architecture andaim at obtaining crisp experimental results and a deeper un-derstanding: either the policy greedy in the learned valuefunction achieves close to 100% generalization over instanceslarger than those used in training, or the failure must be under-stood, and possibly fixed, logically. For this, we exploit therelation established between the expressive power of GNNsand the C2 fragment of first-order logic (namely, FOL with2 variables and counting quantifiers). We find for examplethat domains with general policies that require more expres-sive features can be solved with GNNs once the states are ex-tended with suitable â€derived atoms†encoding role composi-tions and transitive closures that do not fit into C2. The workfollows an existing approach based on GNNs for learning op-timal general policies in a supervised fashion, but the learnedpolicies are no longer required to be optimal (which expandsthe scope, as many planning domains do not have general op-timal policies) and are learned without supervision. Interest-ingly, value-based reinforcement learning methods that aimto produce optimal policies, do not always yield policies thatgeneralize, as the goals of optimality and generality are inconflict in domains where optimal planning is NP-hard.

[376] Simon Ståhlberg, Blai Bonet and Hector Geffner. 2022.
Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits.
In Akshat Kumar, Sylvie Thiébaux, Pradeep Varakantham, William Yeoh (eds), editors, Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (ICAPS 2022), pages 629–637. AAAI Press. ISBN: 9781577358749.
DOI: 10.1609/icaps.v32i1.19851.
Fulltext: https://doi.org/10.1609/icaps.v32i1.1985...
Förlagets fulltext / Publisher's full text: https://ojs.aaai.org/index.php/ICAPS/iss...

It has been recently shown that general policies for many clas-sical planning domains can be expressed and learned in termsof a pool of features defined from the domain predicates usinga description logic grammar. At the same time, most descrip-tion logics correspond to a fragment of k-variable countinglogic (Ck ) for k = 2, that has been shown to provide a tightcharacterization of the expressive power of graph neural net-works. In this work, we make use of these results to under-stand the power and limits of using graph neural networks(GNNs) for learning optimal general policies over a numberof tractable planning domains where such policies are knownto exist. For this, we train a simple GNN in a supervised man-ner to approximate the optimal value function V ∗(s) of anumber of sample states s. As predicted by the theory, it is ob-served that general optimal policies are obtained in domainswhere general optimal value functions can be defined withC2 features but not in those requiring more expressive C3 fea-tures. In addition, it is observed that the features learned are inclose correspondence with the features needed to express V ∗in closed form. The theory and the analysis of the domainslet us understand the features that are actually learned as wellas those that cannot be learned in this way, and let us movein a principled manner from a combinatorial optimization ap-proach to learning general policies to a potentially, more ro-bust and scalable approach based on deep learning.

[375] Daniel Gnad, Álvaro Torralba and Daniel Fi?er. 2022.
Beyond Stars ? Generalized Topologies for Decoupled Search.
In Akshat Kumar, Sylvie Thiébaux, Pradeep Varakantham, William Yeoh (eds), editors, Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, ICAPS 2022, pages 110–118. AAAI Press. ISBN: 978-1-57735-874-9.
DOI: 10.1609/icaps.v32i1.19791.
Fulltext: https://doi.org/10.1609/icaps.v32i1.1979...

Decoupled search decomposes a classical planning task by partitioning its variables such that the dependencies between the resulting factors form a star topology. In this topology, a single center factor can interact arbitrarily with a set of leaf factors. The leaves, however, can interact with each other only indirectly via the center. In this work, we generalize this structural requirement and allow arbitrary topologies. The components must not overlap, i.e., each state variable is assigned to exactly one factor, but the interaction between factors is not restricted. We show how this generalization is connected to star topologies, which implies the correctness of decoupled search with this novel type of decomposition. We introduce factoring methods that automatically identify these topologies on a given planning task. Empirically, the generalized factorings lead to increased applicability of decoupled search on standard IPC benchmarks, as well as to superior performance compared to known factoring methods.

[374] Silvan Sievers, Daniel Gnad and Alvaro Torralba. 2022.
Additive Pattern Databases for Decoupled Search.
In Lukas Chrpa and Alessandro Saetti, editors, Proceedings of the Fifteenth International Symposium on Combinatorial Search, SOCS 2022, pages 180–189. ISBN: 1-57735-873-2.
Förlagets fulltext / Publisher's full text: https://ojs.aaai.org/index.php/SOCS/arti...

Abstraction heuristics are the state of the art in optimal classical planning asheuristic search. Despite their success for explicit-state search, though,abstraction heuristics are not available for decoupled state-space search, anorthogonal reduction technique that can lead to exponential savings by decomposingplanning tasks. In this paper, we show how to compute pattern database (PDB)heuristics for decoupled states. The main challenge lies in how to additively employmultiple patterns, which is crucial for strong search guidance of the heuristics. Weshow that in the general case, for arbitrary collections of PDBs, computing theheuristic for a decoupled state is exponential in the number of leaf components ofdecoupled search. We derive several variants of decoupled PDB heuristics that allowto additively combine PDBs avoiding this blow-up and evaluate them empirically.

[373] 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.

[372] Filip Strömbäck, Linda Mannila and Mariam Kamkar. 2022.
Pilot Study of Progvis: A Visualization Tool for Object Graphs and Concurrency via Shared Memory.
In PROCEEDINGS OF THE 24TH AUSTRALASIAN COMPUTING EDUCATION CONFERENCE, ACE 2022, pages 123–132. Association for Computing Machinery (ACM). ISBN: 9781450396431.
DOI: 10.1145/3511861.3511885.
fulltext:print: https://liu.diva-portal.org/smash/get/di...

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.

2021
[371] Peter Jonsson, Victor Lagerkvist and Sebastian Ordyniak. 2021.
Reasoning Short Cuts in Infinite Domain Constraint Satisfaction: Algorithms and Lower Bounds for Backdoors.
In Proceedings of the 27th International Conference on Principles and Practice of Constraint Programming, pages 32:1–32:20. In series: Leibniz International Proceedings in Informatics (LIPIcs) #32. Schloss Dagstuhl -- Leibniz-Zentrum für Informatik. ISBN: 9783959772112.
DOI: 10.4230/LIPIcs.CP.2021.32.

A backdoor in a finite-domain CSP instance is a set of variables where each possible instantiation moves the instance into a polynomial-time solvable class. Backdoors have found many applications in artificial intelligence and elsewhere, and the algorithmic problem of finding such backdoors has consequently been intensively studied. Sioutis and Janhunen (KI, 2019) have proposed a generalised backdoor concept suitable for infinite-domain CSP instances over binary constraints. We generalise their concept into a large class of CSPs that allow for higher-arity constraints. We show that this kind of infinite-domain backdoors have many of the positive computational properties that finite-domain backdoors have: the associated computational problems are fixed-parameter tractable whenever the underlying constraint language is finite. On the other hand, we show that infinite languages make the problems considerably harder.

[370] Leif Eriksson and Victor Lagerkvist. 2021.
Improved Algorithms for Allen?s Interval Algebra: a Dynamic Programming Approach.
In Proceedings of the 30th International Joint Conference on Artificial Intelligence, pages 1873–1879.
DOI: 10.24963/ijcai.2021/258.

The constraint satisfaction problem (CSP) is an important framework in artificial intelligence used to model e.g. qualitative reasoning problems such as Allen's interval algebra A. There is strong practical incitement to solve CSPs as efficiently as possible, and the classical complexity of temporal CSPs, including A, is well understood. However, the situation is more dire with respect to running time bounds of the form O(f(n)) (where n is the number of variables) where existing results gives a best theoretical upper bound 2^O(n * log n) which leaves a significant gap to the best (conditional) lower bound 2^o(n). In this paper we narrow this gap by presenting two novel algorithms for temporal CSPs based on dynamic programming. The first algorithm solves temporal CSPs limited to constraints of arity three in O(3^n) time, and we use this algorithm to solve A in O((1.5922n)^n) time. The second algorithm tackles A directly and solves it in O((1.0615n)^n), implying a remarkable improvement over existing methods since no previously published algorithm belongs to O((cn)^n) for any c. We also extend the latter algorithm to higher dimensions box algebras where we obtain the first explicit upper bound.

[369] 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.
fulltext:print: https://liu.diva-portal.org/smash/get/di...

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 ‘harder’ 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.

[368] 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.

[367] Johan Källström, 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.

[366] 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.

[365] 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.

[364] 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.

[363] Fredrik Präntare, 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.
DOI: 10.1609/aaai.v35i13.17349.
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]
Fulltext: https://doi.org/10.1609/aaai.v35i13.1734...

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.

[362] Simon Ståhlberg, Guillem Francès 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. ISBN: 978-0-9992411-9-6.
fulltext:print: http://liu.diva-portal.org/smash/get/div...

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.

[361] 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 , pages 271–280. In series: Proceedings of the International Conference on Automated Planning and Scheduling #??. AAAI Press. ISBN: 978-1-57735-867-1.
Publisher´s full text: 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.

[360] Álvaro Torralba, Jendrik Seipp and Silvan Sievers. 2021.
Automatic Instance Generation for Classical Planning.
In Susanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo, editors, Proceedings of the International Conference on Automated Planning and Scheduling, pages 376–384. AAAI Press. ISBN: 978-1-57735-867-1.
DOI: 10.1609/icaps.v31i1.15983.

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.

[359] 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. In series: Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning #??. International Joint Conferences on Artificial Intelligence Organization (IJCAI Organization). ISBN: 978-1-956792-99-7.

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.

[358] 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.
Länk 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.

[357] 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.

[356] Full text  Fredrik Präntare 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.

2020
[355] Linda Mannila, Fredrik Heintz, Susanne Kjällander and Anna+ Åkerfeldt. 2020.
Programming in primary education: Towards a research based assessment framework.
In WiPSCE '20: Proceedings of the 15th Workshop on Primary and Secondary Computing Education. ACM Digital Library. ISBN: 9781450387590.
DOI: 10.1145/3421590.3421598.

In March 2017, the Swedish government decided to introduce digital competence - including programming - in primary school. As a consequence, every math and technology teacher in grades 1-9 in Sweden is expected to integrate programming in their teaching. Furthermore, the Swedish school law requires that teaching is based on scientific evidence and proven experience. In addition to professional development for teachers, it is hence crucial to also conduct research on different aspects of programming in the classroom. In this paper, we describe the process of developing a scientifically grounded instrument for assessing students' programming skills, as part of a longitudinal research project investigating how students in primary school learn programming. We also present the main findings related to the suitability of the instrument based on a pilot study conducted in spring 2019, collecting data from 310 students.

[354] 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.

[353] 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.
fulltext:postprint: http://liu.diva-portal.org/smash/get/div...

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.

[352] Fredrik Präntare, Mattias Tiger, David Bergström, 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.

[351] 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.
DOI: 10.18653/v1/2020.coling-main.450.
Fulltext: https://doi.org/10.18653/v1/2020.coling-...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

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 “extracting the linguistic structure encoded in the representations†and “learning the probing task,†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’s 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.

[350] 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.

[349] 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.

[348] Full text  Johan Källström and Fredrik Heintz. 2020.
Agent Coordination in Air Combat Simulation using Multi-Agent Deep Reinforcement Learning.
In 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: https://liu.diva-portal.org/smash/get/di...

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.

[347] Veronika Domova, Erik Gärtner, Fredrik Präntare, Martin Pallin, Johan Källström 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.

[346] 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....

[345] 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....

[344] 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.

[343] 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.

[342] Full text  Johan Källström 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.

[341] Full text  Johan Källström. 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. The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). ISBN: 978-1-4503-7518-4.
Link: http://www.ifaamas.org/Proceedings/aamas...
fulltext:print: https://liu.diva-portal.org/smash/get/di...

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.

[340] Filip Strömbäck, 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.

[339] Olov Andersson, Per Sidén, 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
[338] 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.

[337] 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.

[336] 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.

[335] 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.

[334] Barbara Dunin-Keplicz, Inga Rüb 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)

[333] Full text  David Bergström, 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), Umeå, 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.

[332] 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.

[331] Full text  Johan Källström 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.

[330] Full text  Johan Källström 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: Linköping 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.

[329] Filip Strömbäck, 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.

[328] Full text  Johan Källström 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.

[327] 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.
DOI: 10.1609/aaai.v33i01.33012760.
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 ‘true’ 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
[326] Linda Mannila, Lars-Åke Nordén and Arnold Pears. 2018.
Digital Competence, Teacher Self-Efficacy and Training Needs.
In ICER '18: Proceedings of the 2018 ACM Conference on International Computing Education Research, pages 78–85. ACM Digital Library. ISBN: 9781450356282.
DOI: 10.1145/3230977.3230993.

Computing related content is introduced in school curricula all over the world, placing new requirements on school teachers and their knowledge. Little attention has been paid to fostering the skills and attitudes required to teach the new content. This involves not only traditional computing topics, such as algorithms or programming, but also the role of technology in society as well as questions related to ethics, safety and integrity. As technology develops at a fast rate, so does the content to be taught. Learning computing content through isolated in-service training initiatives is by no means enough, but rather, teachers need to develop confidence to independently and continuously explore what is new, what is relevant and how to include digital competence in their teaching. Teachers' self-efficacy is hence of crucial importance. In a previous article \citenorden2017 we described the development of a self-efficacy scale for teachers, focusing on digital competence as described in EU's framework DigComp 2.0. In this paper, we extend that work by analysing 530 teachers' responses collected in Autumn 2017 during a series of workshops and other professional development events. Our goal was to collect baseline data, painting a picture of teachers' current self-efficacy levels in order to facilitate follow-up studies. In addition, our results also point out challenging areas, consequently providing important insight into what topics and themes should be emphasized in professional development initiatives.

[325] Linda Mannila, Fredrik Heintz, Susanne Kjällander and Anna Åkerfeldt. 2018.
Programming in Primary School: Towards a Research-Based Assessment Instrument.
In WiPSCE '20: Proceedings of the 15th Workshop on Primary and Secondary Computing Education. In series: ACM International Conference Proceeding Series #10. ACM Digital Library. ISBN: 9781450387590.
DOI: 10.1145/3421590.3421598.

In March 2017, the Swedish government decided to introduce digital competence - including programming - in primary school. As a consequence, every math and technology teacher in grades 1-9 in Sweden is expected to integrate programming in their teaching. Furthermore, the Swedish school law requires that teaching is based on scientific evidence and proven experience. In addition to professional development for teachers, it is hence crucial to also conduct research on different aspects of programming in the classroom. In this paper, we describe the process of developing a scientifically grounded instrument for assessing students' programming skills, as part of a longitudinal research project investigating how students in primary school learn programming. We also present the main findings related to the suitability of the instrument based on a pilot study conducted in spring 2019, collecting data from 310 students.

[324] Fredrik Löfgren, 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.

[323] 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.

[322] 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.

[321] 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’s interpretations of autonomous car behavior, building on our previous research on human-robot interaction, participants were presented with (1) images of cars – either with or without a driver – 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.

[320] Lukasz Bialek, Barbara Dunin-Keplicz and Andrzej Szalas. 2018.
Towards a Paraconsistent Approach to Actions in Distributed Information-Rich Environments.
In Mirjana Ivanović, Costin Bădică, Jürgen Dix, Zoran Jovanović, Michele Malgeri, MiloÅ¡ Savić, 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 Bel \" role=\"presentation\"> 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.

[319] Full text  Fredrik Präntare 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.

[318] 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.

[317] Full text  Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2018.
Planning with Temporal Uncertainty, Resources and Non-Linear Control Parameters.
In Mathijs de Weerdt, Sven Koenig, Gabriele Röger, 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.

[316] 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.

[315] 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.

[314] 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
[313] 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.

[312] 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.

[311] 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).

[310] 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.

[309] 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.

[308] 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.

[307] Full text  Fredrik Präntare, Ingemar Ragnemalm and Fredrik Heintz. 2017.
An Algorithm for Simultaneous Coalition Structure Generation and Task Assignment.
In Bo An, Ana Bazzan, João 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.

[306] Full text  Fredrik Heintz, Linda Mannila, Lars-Åke Nordén, Peter Parnes and Regnell Björn. 2017.
Introducing Programming and Digital Competence in Swedish K?9 Education.
In Valentina DagienÄ— 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.

[305] Fredrik Heintz and Fredrik Löfgren. 2017.
Linköping 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.

[304] 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.

[303] 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.

2016
[302] Fredrik Heintz and Fredrik Löfgren. 2016.
Linköping 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.

[301] Gustav Häger, 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.

[300] 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.

[299] Full text  Patrick Doherty, Jonas Kvarnström 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.

[298] Full text  Fredrik Heintz, Linda Mannila and Tommy Färnqvist. 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–12 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–12 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.

[297] 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.

[296] 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.

[295] Full text  Cyrille Berger, Mariusz Wzorek, Jonas Kvarnström, 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.

[294] 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.

[293] 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.

[292] 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.

[291] 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.

[290] 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.

[289] 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.

[288] Full text  Patrick Doherty, Jonas Kvarnström, 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.

[287] 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.

[286] 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.

[285] Full text  Tommy Färnqvist, 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.

2015
[284] Fredrik Löfgren, 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 â€LiU Robotics†team. In thisdocument we present ourselves and what we want to achieve byour participation in the conference and competition

[283] Full text  Tommy Färnqvist, 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 för Sveriges ingenjörsutbildningar (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.

[282] Full text  Michaël Grimsberg, Fredrik Heintz, Viggo Kann, Inger Erlander Klein and Lars Öhrström. 2015.
Vem styr egentligen grundutbildningen?.
In Proceedings of 5:e Utvecklingskonferensen för Sveriges ingenjörsutbildningar (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.

[281] Fredrik Heintz, Aseel Berglund, Björn Hedin and Viggo Kann. 2015.
En jämförelse mellan programsamanhållande kurser vid KTH och LiU.
In Proceedings of 5:e Utvecklingskonferensen för Sveriges ingenjörsutbildningar (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.

[280] Fredrik Heintz, Tommy Färnqvist and Jesper Thorén. 2015.
Programutvecklingsstrategier för att öka kopplingen mellan programmering och matematik.
In Proceedings of 5:e Utvecklingskonferensen för Sveriges ingenjörsutbildningar (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.

[279] Full text  Mikael Nilsson, Jonas Kvarnström and Patrick Doherty. 2015.
Revisiting Classical Dynamic Controllability: A Tighter Complexity Analysis.
In Béatrice 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.

[278] 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.
länk 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.

[277] 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).

[276] 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 Fermé, 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).

[275] Full text  Fredrik Heintz, Linda Mannila, Karin Nygårds, Peter Parnes and Björn 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.

[274] 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.

[273] Full text  Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg, Karl Granström, Fredrik Heintz, Piotr Rudol, Mariusz Wzorek, Jonas Kvarnström 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

[272] 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
[271] 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.

[270] 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.

[269] 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.

[268] 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. Linköping University has therefore developed a completely new course “Professionalism for Engineers†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.

[267] 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.

[266] 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.

[265] 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.

[264] 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.

[263] 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.

[262] 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.

[261] Full text  Mattias Tiger and Fredrik Heintz. 2014.
Towards Learning and Classifying Spatio-Temporal Activities in a Stream Processing Framework.
In Ulle Endriss and João 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.

[260] Oleg Burdakov, Patrick Doherty and Jonas Kvarnström. 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.

[259] 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.

[258] 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.

[257] Full text  Mikael Nilsson, Jonas Kvarnström 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.

[256] Mikael Nilsson, Jonas Kvarnström 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) – 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 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.

[255] Full text  Mikael Nilsson, Jonas Kvarnström 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) – executable regardless of the outcomesof uncontrollable durations – 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.

[254] 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.

2013
[253] 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) , aâ‰Ì¸b . 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 “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. In the long version of this paper, we present the first algorithm with PTime data complexity for checking satisfiability of HornDL knowledge bases.

[252] Barbara Dunin-Keplicz, Linh Anh Nguyen and Andrzej Szalas. 2013.
Horn-TeamLog: A Horn Fragment of TeamLog with PTime Data Complexity.
In Costin BÇŽdicÇŽ, 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-Kęplicz and Verbrugge is used to express properties of agents’ 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.

[251] 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.

[250] 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.

[249] 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.

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

[247] Fredrik Heintz and Inger Erlander Klein. 2013.
Civilingenjör i Mjukvaruteknik vid Linköpings universitet: mål, design och erfarenheter.
In S. Vikström, R. Andersson, F. Georgsson, S. Gunnarsson, J. Malmqvist, S. PÃ¥lsson och D. Raudberget, editors, Proceedings of 4:de Utvecklingskonferensen för Sveriges ingenjörsutbildningar (UtvSvIng). In series: UMINF #13:21.

Hösten 2013 startade Linköpings universitet den första civilingenjörsutbildningen i Mjukvaruteknik. Utbildningens mål är att bland annat att ge ett helhetsperspektiv på modern storskalig mjukvaruutveckling, ge en gedigen grund i datavetenskap och computational thinking samt främja entreprenörskap och innovation. Studenternas gensvar har varit över förväntan med över 600 sökande till de 30 platserna varav 134 förstahandssökande. Här presenterar vi programmets vision, mål, designprinciper samt det färdiga programmet. En viktig förebild är ACM/IEEE Computer Science Curricula som precis kommit i en ny uppdaterad version. Tre pedagogiska idéer vi har följt är (1) att använda projektkurser för att integrera teori och praktik samt ge erfarenhet i den vanligaste arbetsformen i näringslivet; (2) att undervisa i flera olika programspråk och flera olika programutvecklingsmetodiker för att ge en plattform att ta till sig det senaste på området; och (3) att införa en programsammanhållande kurs i ingenjörsprofessionalism i årskurs 1–3 som ger studenterna verktyg att reflektera över sitt eget lärande, att jobba i näringslivet samt sin professionella yrkesroll. Artikeln avslutas med en diskussion om viktiga aspekter som computational thinking och ACM/IEEE CS Curricula.

[246] Fredrik Heintz and Tommy Färnqvist. 2013.
Återkoppling genom automaträttning.
In Proceedings of 4:de Utvecklingskonferensen för Sveriges ingenjörsutbildningar (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.

[245] 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, “chronic emergencies†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.

[244] 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.

[243] 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.

[242] 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.

[241] 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.

[240] 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.

[239] 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.

[238] 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.

[237] Full text  Håkan Warnquist, Jonas Kvarnström 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.

[236] Full text  Mikael Nilsson, Jonas Kvarnström 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 – executable regardless of the outcomes of uncontrollable durations – 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.

[235] 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.

[234] 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.

[233] 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.

[232] 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.

2012
[231] Patrick Doherty, Fredrik Heintz and David Landén. 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.

[230] David Landén, 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.

[229] 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.

[228] 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.

[227] 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 “SHERPA†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 “busy geniusâ€, working in team with the ground vehicle, as the “intelligent donkeyâ€, and with the aerial platforms, i.e. the “trained wasps†and “patrolling hawksâ€. Indeed, the research activity focuses on how the “busy genius†and the “SHERPA animals†interact and collaborate with each other, with their own features and capabilities, toward the achievement of a common goal.

[226] 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.

[225] 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.

[224] 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.

[223] Full text  Fredrik Heintz and Tommy Färnqvist. 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.

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

[221] 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
find book in another country/hitta boken i ett annat land: http://www.worldcat.org/search?q=Agent+a...

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.

[220] 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). Linköping 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.

[219] Full text  Patrick Doherty, Jonas Kvarnström 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
[218] 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 #??.

[217] Full text  Jonas Kvarnström. 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.

[216] Full text  Patrick Doherty, Fredrik Heintz and David Landén. 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...

[215] 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.

[214] 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.

[213] 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.

[212] 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. Ã…gotnes 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.

[211] 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> + </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> + </sup> that still have PTime data complexity.

[210] 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.

2010
[209] 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.

[208] Cyrille Berger and Simon Lacroix. 2010.
DSeg: Détection directe de segments dans une image.
In 17ème congrès 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.

[207] 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.

[206] Full text  Patrick Doherty, Jonas Kvarnström, Fredrik Heintz, David Landén 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 für 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.

[205] 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.

[204] Full text  Mariusz Wzorek, Jonas Kvarnström and Patrick Doherty. 2010.
Choosing Path Replanning Strategies for Unmanned Aircraft Systems.
In Ronen Brafman, Héctor Geffner, Jörg 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.

[203] Full text  Fredrik Heintz, Jonas Kvarnström 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 für 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.

[202] Full text  Fredrik Heintz, Jonas Kvarnström 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.

[201] Full text  Fredrik Heintz, Jonas Kvarnström 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.

[200] 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.

[199] Full text  Jonas Kvarnström 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.

[198] Full text  Per-Magnus Olsson, Jonas Kvarnström, 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.

[197] Full text  Håkan Warnquist, Jonas Kvarnström 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.

[196] Full text  Jonas Kvarnström. 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: Linköping Electronic Conference Proceedings #48. Linköping University Electronic Press, Linköpings 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.

[195] 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?

[194] Full text  Oleg Burdakov, Patrick Doherty, Kaj Holmberg, Jonas Kvarnström 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
[193] 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.

[192] 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.

[191] 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.

[190] Full text  Teresa Vidal-Calleja, Cyrille Berger, Joan Solà 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 Plücker 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.

[189] 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.

[188] Full text  Anna Pernestål, Håkan 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.

[187] Full text  Håkan Warnquist, Jonas Kvarnström 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.

[186] Full text  Håkan Warnquist, Anna Pernestål 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.

[185] Full text  Martin Magnusson, David Landén 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).

[184] Full text  Martin Magnusson and Patrick Doherty. 2009.
Planning Speech Acts in a Logic of Action and Change.
In Fredrik Heintz and Jonas Kvarnström, editors, The Swedish AI Society Workshop 2009, SAIS 2009, pages 39–48. In series: Linköping Electronic Conference Proceedings #35. Linköping University Electronic Press, Linköpings 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.

[183] Full text  Fredrik Heintz, Jonas Kvarnström 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.

[182] 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.

[181] Full text  Martin Magnusson, Jonas Kvarnström 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.

[180] Full text  Fredrik Heintz, Jonas Kvarnström 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...

[179] 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.

[178] 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.

2008
[177] 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.

[176] Cyrille Berger and Simon Lacroix. 2008.
Modélisation de l'environnement par facettes planes pour la Cartographie et la Localisation Simultanées par stéréovision.
In Reconnaissance des Formes et Intelligence Artificielle (RFIA).

[175] 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.

[174] 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>

[173] 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.

[172] 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.

[171] Full text  Håkan 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.

[170] Full text  Håkan Warnquist, Mattias Nyberg and Petter Säby. 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.

[169] 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.

[168] Full text  Gianpaolo Conte, Maria Hempel, Piotr Rudol, David Lundström, 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.

[167] 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.

[166] 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.

[165] Patrick Doherty and Andrzej Szalas. 2008.
Reasoning with Qualitative Preferences and Cardinalities Using Generalized Circumscription.
In Gerhard Brewka, Jérôme 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.

[164] 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.

[163] 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.

[162] 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.

[161] Full text  Martin Magnusson, David Landén 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.

[160] 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.

[159] 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.

[158] Full text  Fredrik Heintz, Jonas Kvarnström 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.

[157] Full text  Jonas Kvarnström, 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.

[156] 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.

[155] Rickard Karlsson, Thomas Schön, David Törnqvist, 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.

[154] 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.

[153] 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.

[152] 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.

[151] Rickard Karlsson, Thomas Schön, David Törnqvist, Gianpaolo Conte and Fredrik Gustafsson. 2008.
Utilizing Model Structure for Efficient Simultaneous Localization and Mapping for a UAV Application.
In Proceedings of Reglermöte 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.

[150] 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.

[149] 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.

[148] Full text  Fredrik Heintz, Jonas Kvarnström 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.

2007
[147] 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.

[146] 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, “compatible†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.

[145] 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.

[144] 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.

[143] David Lawrence, Erik Sandewall and Peter Berkesand. 2007.
A Swedish Journal Publication Service.
In Högskolor och samhälle 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.

[142] Full text  Simone Duranti, Gianpaolo Conte, David Lundström, 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.

[141] 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.

[140] 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.

[139] 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.

[138] Full text  Luis Mejias, Pascual Campoy, Iván F. Mondragón 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.

[137] 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.

[136] 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.

[135] 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.

2006
[134] Full text  Alexander Kleiner, Christian Dornhege, Rainer Kümmerle, Michael Ruhnke, Bastian Steder, Bernhard Nebel, Patrick Doherty, Mariusz Wzorek, Piotr Rudol, Gianpaolo Conte, Simone Duranti and David Lundström. 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.

[133] 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].

[132] 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.

[131] 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.

[130] 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.

[129] Full text  Mariusz Wzorek, David Landén 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

[128] 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.

[127] 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.

[126] Full text  H.Joe Steinhauer. 2006.
Qualitative Communication about Object Scenes.
In Proceedings of the 29th Annual German Conference on Artificial Intelligence (KI).

[125] 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.

[124] 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).

[123] 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.

[122] 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.

[121] 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.

[120] Björn Hägglund 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.

[119] 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.

2005
[118] Full text  Peter Andersson. 2005.
Hazard: a Framework Towards Connecting Artificial Intelligence and Robotics.
In IJCAI Workshop on Reasoning, Representation and Learning in Computer Games.

[117] Full text  Ewa Madalinska-Bugaj and Witold Lukaszewicz. 2005.
Belief revision revisited.
In Advances in Artificial Intelligence: Proceedings of the 4th Mexican International Conference on Artificial Intelligence (MICAI), pages 31–40. In series: Lecture Notes in Computer Science #3789. Springer.
DOI: 10.1007/11579427_4.

In this paper, we propose a new belief revision operator, together with a method of its calculation. Our formalization differs from most of the traditional approaches in two respects. Firstly, we formally distinguish between defeasible observations and indefeasible knowledge about the considered world. In particular, our operator is differently specified depending on whether an input formula is an observation or a piece of knowledge. Secondly, we assume that a new observation, but not a new piece of knowledge, describes exactly what a reasoning agent knows at the moment about the aspect of the world the observation concerns.

[116] Full text  Patrick Doherty, Andrzej Szalas and Witold Lukaszewicz. 2005.
Similarity, approximations and vagueness.
In Dominik Slezak, Guoyin Wang, Marcin S. Szczuka, Ivo Düntsch, Yiyu Yao, editors, Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC), pages 541–550. In series: Lecture Notes in Artificial Intelligence #3641. Springer. ISBN: 3-540-28653-5.
DOI: 10.1007/11548669_56.

The relation of similarity is essential in understanding and developing frameworks for reasoning with vague and approximate concepts. There is a wide spectrum of choice as to what properties we associate with similarity and such choices determine the nature of vague and approximate concepts defined in terms of these relations. Additionally, robotic systems naturally have to deal with vague and approximate concepts due to the limitations in reasoning and sensor capabilities. Halpern [1] introduces the use of subjective and objective states in a modal logic formalizing vagueness and distinctions in transitivity when an agent reasons in the context of sensory and other limitations. He also relates these ideas to a solution to the Sorities and other paradoxes. In this paper, we generalize and apply the idea of similarity and tolerance spaces [2,3,4,5], a means of constructing approximate and vague concepts from such spaces and an explicit way to distinguish between an agent’s objective and subjective states. We also show how some of the intuitions from Halpern can be used with similarity spaces to formalize the above-mentioned Sorities and other paradoxes.

[115] Full text  Fredrik Heintz and Patrick Doherty. 2005.
A knowledge processing middleware framework and its relation to the JDL data fusion model.
In The 8th International Conference on Information Fusion,2005.

[114] Michali Grabowski and Andrzej Szalas. 2005.
A Technique for Learning Similarities on Complex Structures with Applications to Extracting Ontologies.
In Proceedings of the 3rd Atlantic Web Intelligence Conference (AWIC), pages 991–995. In series: Lecture Notes in Computer Science #3528. Springer.
DOI: 10.1007/11495772_29.

A general similarity-based algorithm for extracting ontologies from data has been provided in [1]. The algorithm works over arbitrary approximation spaces, modeling notions of similarity and mereological part-of relations (see, e.g., [2, 3, 4, 5]). In the current paper we propose a novel technique of machine learning similarity on tuples on the basis of similarities on attribute domains. The technique reflects intuitions behind tolerance spaces of [6] and similarity spaces of [7]. We illustrate the use of the technique in extracting ontologies from data.

[113] Full text  Erik Johan Sandewall. 2005.
Actions as a Basic Software Concept in the Leonardo Computation System.
In IJCAI 2005 Workshop on Nonmonotonic Reasoning, Action and Change,2005.

[112] Full text  Erik Johan Sandewall. 2005.
Integration of Live Video in a System for Natural Language Dialog with a Robot.
In Proceedings of the 9th workshop on the semantics and pragmatics of dialogue (SemDial).

[111] Full text  Mariusz Wzorek and Patrick Doherty. 2005.
Reconfigurable path planning for an autonomous unmanned aerial vehicle.
In National Swedish Workshop on Autonomous Systems, SWAR 05,2005.

[110] Full text  Mariusz Wzorek and Patrick Doherty. 2005.
Preliminary report: Reconfigurable path planning for an autonomous unmanned aerial vehicle.
In Proceedings of the 24th Annual Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG).

[109] Patrick Doherty. 2005.
Knowledge representation and unmanned aerial vehicles.
In Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT), pages 9–16. IEEE Computer Society. ISBN: 0-7695-2416-8.
DOI: 10.1109/IAT.2005.93.

Knowledge representation technologies play a fundamental role in any autonomous system that includes deliberative capability and that internalizes models of its internal and external environments. Integrating both high- and low-end autonomous functionality seamlessly in autonomous architectures is currently one of the major open problems in robotics research. UAVs offer especially difficult challenges in comparison with ground robotic systems due to the often tight time constraints and safety considerations that must be taken into account. This article provides an overview of some of the knowledge representation technologies and deliberative capabilities developed for a fully deployed autonomous unmanned aerial vehicle system to meet some of these challenges.

[108] Full text  Patrik Haslum, Blai Bonet and Hector Geffner. 2005.
New Admissible Heuristics for Domain-Independent Planning.
In Proceedings of the 20th national ´Conference on Artificial Intelligence (AAAI). AAAI Press. ISBN: 1-57735-236-X.

Admissible heuristics are critical for effective domain-independent planning when optimal solutions must be guaranteed. Two useful heuristics are the <em>h<sup>m</sup></em> heuristics, which generalize the reachability heuristic underlying the planning graph, and pattern database heuristics. These heuristics, however, have serious limitations: reachability heuristics capture only the cost of critical paths in a relaxed problem, ignoring the cost of other relevant paths, while PDB heuristics, additive or not, cannot accommodate too many variables in patterns, and methods for automatically selecting patterns that produce good estimates are not known.We introduce two refinements of these heuristics: First, the additive <em>h<sup>m</sup></em> heuristic which yields an admissible sum of <em>h<sup>m</sup></em> heuristics using a partitioning of the set of actions. Second, the constrained PDB heuristic which uses constraints from the original problem to strengthen the lower bounds obtained from abstractions.The new heuristics depend on the way the actions or problem variables are partitioned. We advance methods for automatically deriving additive <em>h<sup>m</sup></em> and PDB heuristics from STRIPS encodings. Evaluation shows improvement over existing heuristics in several domains, although, not surprisingly, no heuristic dominates all the others over all domains.

[107] Full text  Fredrik Heintz and Patrick Doherty. 2005.
A Knowledge processing Middleware Framework and its Relation to the JDL Data Fusion model.
In SWAR 05,2005, pages 50–51.

[106] Full text  Fredrik Heintz and Patrick Doherty. 2005.
A Knowledge processing Middleware Framework and its Relation to the JDL Data Fusion model.
In 3rd joint SAIS-SSL event on Artificial Intelligence an Learning Systems,2005. Mälardalens University.

[105] Peter Andersson. 2005.
Hazard: A Framework Towards Connecting Artificial Intelligence and Robotics.
In Proceedings of the 1st International Workshop on Multi-Agent Robotic Systems (MARS). INSTICC PRESS.

[104] Full text  Per Nyblom. 2005.
Handling Uncertainty by Interleaving Cost-Aware Classical Planning with Execution.
In 3rd joint SAIS-SSL event on Artificial Intelligence and Learning Systems,2005.

[103] Full text  Martin Magnusson, Patrick Doherty and Andrzej Szalas. 2005.
An Experimental Platform for Approximate Databases.
In 3rd joint SAIS-SSL event on Artificial Intelligence and Learning Systems,2005.

[102] Full text  Per Olof Pettersson and Patrick Doherty. 2005.
Probabilistic Roadmap Based Path Planning for an Autonomous Unmanned Helicopter.
In Peter Funk, Thorsteinn Rögnvaldsson and Ning Xiong, editors, Proceedings of the 3rd joint SAIS-SSLS event on Artificial Intelligence and Learning Systems (SAIS-SSLS). Mälardalen University.

The emerging area of intelligent unmanned aerialvehicle (UAV) research has shown rapid development in recentyears and offers a great number of research challenges for artificialintelligence. For both military and civil applications, thereis a desire to develop more sophisticated UAV platforms wherethe emphasis is placed on development of intelligent capabilities.Imagine a mission scenario where a UAV is supplied with a 3Dmodel of a region containing buildings and road structures andis instructed to fly to an arbitrary number of building structuresand collect video streams of each of the building’s respectivefacades. In this article, we describe a fully operational UAVplatform which can achieve such missions autonomously. Wefocus on the path planner integrated with the platform which cangenerate collision free paths autonomously during such missions.It is based on the use of probabilistic roadmaps. The path plannerhas been tested together with the UAV platform in an urbanenvironment used for UAV experimentation.

[101] Full text  Karolina Eliasson. 2005.
Towards a Robotic Dialogue System with Learning and Planning Capabilities.
In Ingrid Zukerman, Jan Alexandersson , Arne Jönsson, editors, Proceedings of the IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems (KRPDS), pages 1–7.

We present a robotic dialogue system built on casebased reasoning. The system is capable of solving references and manage sub-dialogues in a dialogue with an operator in natural language. The approach to handle dialogue acts and physical acts in a unison manner together with the use of plans and subplans makes the system very flexible. This flexibility is used for learning purposes where the operator teaches the system a new word and the new knowledge can directly be integrated and used in the old plans. The learning from explanation capability makes the system adaptable to the operator's use of language and the domain it is currently operating in. The implementation of a case-based planner suggested in the paper will further increase the learning and adaptation degree.

[100] Full text  Karolina Eliasson. 2005.
Integrating a Discourse Model with a Learning Case-Based Reasoning System.
In Proceedings of the 9th workshop on the semantics and pragmatics of dialogue (SemDial).

We present a discourse model integrated with a case-based reasoning dialogue system which learns from experience. The discourse model is capable of solving references, manage subdialogues and respect the current topic in a dialogue in natural language. The framework is flexible enough not to disturb the learning functions, but allows dynamic changes to a large extent. The system is tested in a traffic surveillance domain together with a simulated UAV and is found to be robust and reliable.

[99] Full text  Karolina Eliasson. 2005.
An Integrated Discourse Model for a Case-Based Reasoning Dialogue System.
In 3rd joint SAIS-SSL event on Artificial Intelligence and Learning Systems,2005.

[98] Full text  H.Joe Steinhauer. 2005.
Towards a Qualitative Model for Natural Language Communication about Vehicle Traffic.
In IJCAI 2005 Workshop on Spatial and Temporal Reasoning,2005.

[97] Full text  H.Joe Steinhauer. 2005.
A Qualitative Model for Natural Language Communication about Vehicle Traffic.
In Proceedings of the AAAI Spring Symposium on Reasoning with Mental and External Diagrams - Computational Modeling and Spatial Assistance, pages 52–57. AAAI Press. ISBN: 978-1-57735-232-7.

In this paper we describe a qualitative approach for natural language communication about vehicle traffic. It is an intuitive and simple model that can be used as the basis for defining more detailed position descriptions and transitions. It can also function as a framework for relating different aggregation levels. We apply a diagrammatic abstraction of traffic that mirrors the different possible interpretations of it and with this the different mental abstractions that humans might make. The abstractions are kept in parallel and according to the communicative context it will be switched to the corresponding interpretation.

2004
[96] Full text  Fredrik Heintz and Patrick Doherty. 2004.
DyKnow: A Framework for Processing Dynamic Knowledge and Object Structures in Autonomous Systems.
In Proceedings of the Second Joint SAIS/SSLS Workshop.

[95] Full text  Patrik Haslum. 2004.
Patterns in Reactive Programs.
In Patrick Doherty, Gerhard Lakemeyer, Angel P. de Pobil, editors, Proceedings of the 4th International Cognitive Robotics Workshop (COGROB), pages 25–29.

In this paper, I explore the idea that there are “patternsâ€,analogous to software design patterns, in the kind of task proceduresthat frequently form the reactive component of architectures for intelligentautonomous systems. The investigation is carried out mainlywithin the context of the WITAS UAV project.

[94] Full text  Patrick Doherty, Steven Kertes, Martin Magnusson and Andrzej Szalas. 2004.
Towards a logical analysis of biochemical pathways.
In José Júlio Alferes and João Alexandre Leite, editors, Proceedings of the 9th European Conference on Logics in Artificial Intelligence (JELIA), pages 667–679. In series: Lecture Notes in Computer Science #3229. Springer. ISBN: 978-3-540-23242-1.
DOI: 10.1007/978-3-540-30227-8_55.

Biochemical pathways or networks are generic representations used to model many different types of complex functional and physical interactions in biological systems. Models based on experimental results are often incomplete, e.g., reactions may be missing and only some products are observed. In such cases, one would like to reason about incomplete network representations and propose candidate hypotheses, which when represented as additional reactions, substrates, products, would complete the network and provide causal explanations for the existing observations. In this paper, we provide a logical model of biochemical pathways and show how abductive hypothesis generation may be used to provide additional information about incomplete pathways. Hypothesis generation is achieved using weakest and strongest necessary conditions which represent these incomplete biochemical pathways and explain observations about the functional and physical interactions being modeled. The techniques are demonstrated using metabolism and molecular synthesis examples.

[93] Full text  Bourhane Kadmiry and P. Bergsten. 2004.
Robust Fuzzy Gain Scheduled visual-servoing with Sampling Time Uncertainties.
In IEEE International Symposium on Intelligent Control ISIC,2004, pages 239–245. In series: International Symposium on Intelligent Control #2004. ISBN: 0-7803-8635-3.
DOI: 10.1109/ISIC.2004.1387689.
Fulltext: https://doi.org/10.1109/ISIC.2004.138768...

This paper addresses the robust fuzzy control problem for discrete-time nonlinear systems in the presence of sampling time uncertainties in a visual-servoing control scheme. The Takagi-Sugeno (T-S) fuzzy model is adopted for the nonlinear geometric model of a pin-hole camera, which presents second-order nonlinearities. The case of the discrete T-S fuzzy system with sampling-time uncertainty is considered and a multi-objective robust fuzzy controller design is proposed for the uncertain fuzzy system. The sufficient conditions are formulated in the form of linear matrix inequalities (LMI). The effectiveness of the proposed controller design methodology is demonstrated through numerical simulation, then tested on a EVI-D31 SONY camera.

[92] Full text  Bourhane Kadmiry and Dimiter Driankov. 2004.
Takagi-Sugeno Fuzzy Gain Scheduling with Sampling-Time Uncertainties.
In IEEE International Conference on Fuzzy Systems Fuzz-IEEE 2004,2004.

This paper addresses the robust fuzzy control problem for discrete-time nonlinear systems in the presence of sampling time uncertainties. The case of the discrete T-S fuzzy system with sampling-time uncertainty is considered and a robust controller design method is proposed. The sufficient conditions and the design procedure are formulated in the form of linear matrix inequalities (LMI). The effectiveness of the proposed controller design methodology is demonstrated of a visual-servoing control problem

[91] Full text  Patrick Doherty. 2004.
Advanced Research with Autonomous Unmanned Aerial Vehicles.
In Proceedings of the 9th International Conference on the Principles of Knowledge Representation and Reasoning, pages 731–732. AAAI Press. ISBN: 978-1-57735-199-3.

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 and knowledge representation. For both military and civilian applications, there is a desire to develop more sophisticated UAV platforms where the emphasis is placed on intelligent capabilities and their integration in complex distributed software architectures. Such architectures should support the integration of deliberative, reactive and control functionalities in addition to the UAV’s integration with larger network centric systems. In my talk I will present some of the research and results from a long term basic research project with UAVs currently being pursued at Linköping University, Sweden. The talk will focus on knowledge representation techniques used in the project and the support for these techniques provided by the software architecture developed for our UAV platform, a Yamaha RMAX helicopter. Additional focus will be placed on some of the planning and execution monitoring functionality developed for our applications in the areas of traffic monitoring, surveying and photogrammetry and emergency services assistance.

[90] Full text  Per Olof Pettersson and Patrick Doherty. 2004.
Probabilistic Roadmap Based Path Planning for an Autonomous Unmanned Aerial Vehicle.
In ICAPS-04 Workshop on Connecting Planning Theory with Practice,2004, pages 49–55.

[89] H.Joe Steinhauer. 2004.
The Qualitative Description of Traffic Maneuvers.
In ECAI Workshop on Spatial and Temporal Reasoning,2004, pages 141–148.

[88] Full text  Patrick Doherty, Patrik Haslum, Fredrik Heintz, Torsten Merz, Per Nyblom, Tommy Persson and Björn Wingman. 2004.
A Distributed Architecture for Autonomous Unmanned Aerial Vehicle Experimentation.
In 7th International Symposium on Distributed Autonomous Robotic Systems,2004. LAAS.

[87] Full text  Fredrik Heintz and Patrick Doherty. 2004.
Managing Dynamic Object Structures using Hypothesis Generation and Validation.
In AAAI Workshop on Anchoring Symbols to Sensor Data,2004, pages 54–62. AAAI Press.

[86] Full text  Fredrik Heintz and Patrick Doherty. 2004.
DyKnow: A Framework for Processing Dynamic Knowledge and Object Structures in Autonomous Systems.
In Barbara Dunin-Keplicz, Andrzej Jankowski, Andrzej Skowron, Marcin Szczuka, editors, Proceedings of the International Workshop on Monitoring, Security, and Rescue Techniques in Multi-Agent Systems (MSRAS), pages 479–492. In series: Advances in Soft Computing #28. Springer. ISBN: 978-3540232452.
DOI: 10.1007/3-540-32370-8_37.

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. These structures must be managed and made accessible to deliberative and reactive functionalities which are dependent on being situationally aware of the changes in both the robotic agent’s embedding and internal environment. DyKnow is a software framework which provides a set of functionalities for contextually accessing, storing, creating and processing such structures. The system is implemented and has been deployed in 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 in execution monitoring and chronicle recognition scenarios for UAV applications.

[85] Torsten Merz. 2004.
Building a System for Autonomous Aerial Robotics Research.
In Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV). Elsevier. ISBN: 008-044237-4.

[84] Full text  Gianpaolo Conte, Simone Duranti and Torsten Merz. 2004.
Dynamic 3D path following for an autonomous helicopter.
In Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV). Elsevier. ISBN: 008-044237-4.
Link to Licentiate Thesis: http://urn.kb.se/resolve?urn=urn:nbn:se:...

A hybrid control system for dynamic path following for an autonomous helicopter is described. The hierarchically structured system combines continuous control law execution with event-driven state machines. Trajectories are defined by a sequence of 3D path segments and velocity profiles, where each path segment is described as a parametric curve. The method can be used in combination with a path planner for flying collision-free in a known environment. Experimental flight test results are shown.

[83] Full text  Patrick Doherty, Steven Kertes, Martin Magnusson and Andrzej Szalas. 2004.
Towards a Logical Analysis of Biochemical Reactions (Extended abstract).
In Ramon López de Mántaras, Lorenza Saitta, editors, Proceedings of the 16th European Conference on Artificial Intelligence (ECAI), pages 997–998. IOS Press. ISBN: 1-58603-452-9.

We provide a logical model of biochemical reactions and show how hypothesis generation using weakest sufficient and strongest necessary conditions may be used to provide additional information in the context of an incomplete model of metabolic pathways.

[82] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2004.
Approximate Databases and Query Techniques for Agents with Heterogenous Perceptual Capabilities.
In Proceedings of the 7th International Conference on Information Fusion, pages 175–182. ISIF. ISBN: 91-7056-115-X.

In this paper, we propose a framework that provides software and robotic agents with the ability to ask approximate questions to each other in the context of heterogeneous and contextually limited perceptual capabilities. The framework focuses on situations where agents have varying ability to perceive their environments. These limitations on perceptual capability are formalized using the idea of tolerance spaces. It is assumed that each agent has one or more approximate databases where approximate relations are represented using intuitions from rough set theory. It is shown how sensory and other limitations can be taken into account when constructing approximate databases for each respective agent. Complex relations inherit the approximativeness inherent in the sensors and primitive relations used in their definitions. Agents then query these databases and receive answers through the filters of their perceptual limitations as represented by tolerance spaces and approximate queries. The techniques used are all tractable.

[81] Full text  Patrick Doherty and Andrzej Szalas. 2004.
On the Correspondence between Approximations and Similarity.
In Shusaku Tsumoto, Roman Slowinski, Jan Komorowski and Jerzy W. Grzymala-Busse, editors, Proceedings of the International Conference on Rough Sets and Current Trends in Computing (RSCTC), pages 143–152. In series: Lecture Notes in Computer Science #3066. Springer.
DOI: 10.1007/978-3-540-25929-9_16.

This paper focuses on the use and interpretation of approximate databases where both rough sets and indiscernibility partitions are generalized and replaced by approximate relations and similarity spaces. Similarity spaces are used to define neighborhoods around individuals and these in turn are used to define approximate sets and relations. There is a wide spectrum of choice as to what properties the similarity relation should have and how this affects the properties of approximate relations in the database. In order to make this interaction precise, we propose a technique which permits specification of both approximation and similarity constraints on approximate databases and automatic translation between them. This technique provides great insight into the relation between similarity and approximation and is similar to that used in modal correspondence theory. In order to automate the translations, quantifier elimination techniques are used.

[80] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2004.
Approximative Query Techniques for Agents with Heterogeneous Ontologies and Perceptive Capabilities.
In Didier Dubois, Christopher A. Welty, Mary-Anne Williams, editors, Proceedings of the 9th International Conference on the Principles of Knowledge Representation and Reasoning, pages 459–468. AAAI Press. ISBN: 978-1-57735-199-3.

In this paper, we propose a framework that provides software and robotic agents with the ability to ask approximate questions to each other in the context of heterogeneous ontologies and heterogeneous perceptive capabilities.The framework combines the use of logic-based techniques with ideas from approximate reasoning. Initial queries by an agent are transformed into approximate queries using weakest sufficient and strongest necessary conditions on the query and are interpreted as lower and upper approximations on the query. Once the base communication ability is provided, the framework is extended to situations where there is not only a mismatch between agent ontologies, but the agents have varying ability to perceive their environments. This will affect each agent’s ability to ask and interpret results of queries. Limitations on perceptive capability are formalized using the idea of tolerance spaces.

[79] Full text  Patrik Haslum. 2004.
Improving Heuristics Through Search.
In Ramon López de Mántaras, Lorenza Saitta, editors, Proceedings of the 16th Eureopean Conference on Artificial Intelligence (ECAI), pages 1031–1032. IOS Press. ISBN: 1-58603-452-9.

We investigate two methods of using limited search to improve admissible heuristics for planning, similar to pattern databases and pattern searches. We also develop a new algorithm for searching AND/OR graphs

2003
[78] Eva-Lena Lengquist Sandelin, Susanna Monemar, Peter Fritzson and Peter Bunus. 2003.
DrModelica - An Interactive Environment for Learning Modelica and Modeling using MathModelica.
In .

This paper states the need for interactive teaching materials for programming languages within the area of modeling and simulation. We propose an interactive teaching material for the modeling language Modelica inspired by existing tutoring systems for Java and Scheme. The purpose of this new teaching material, called DrModelica, is to facilitate the learning of Modelica through an environment that integrates programming, program documentation and visualization. The teaching material is intended to be used for modeling and simulation related courses at the undergraduate and graduate level.

[77] Full text  Eva-Lena Lengquist Sandelin, Susanna Monemar, Peter Fritzson and Peter Bunus. 2003.
DrModelica - A Web-Based Teaching Environment for Modelica.
In Proceedings of the 44th Conference on Simulation and Modeling (SIMS). Malardalen University. ISBN: 91-631-4716-5.

This paper states the need for interactive teaching materials for programming languages within the area of modeling and simulation. We propose an interactive teaching material for the modeling language Modelica inspired by existing tutoring systems for Java and Scheme.The purpose of this new teaching material, called DrModelica, is to facilitate the learning of Modelica in a modeling and simulation environment. We have developed two versions of DrModelica, one that is based on Mathematica and another that is intended for the web. With the web version of DrModelica we hope for an increased usage of Modelica.

[76] Eva-Lena Lengquist Sandelin, Susanna Monemar, Peter Fritzson and Peter Bunus. 2003.
DrModelica - An Interactive Tutoring Environment for Modelica.
In Proceedings of the 3rd International Modelica Conference. Modelica Association.

This paper states the need for interactive teaching materials for programming languages within the area of modeling and simulation. We propose an interactive teaching material for the modeling language Modelica inspired by existing tutoring systems for Java and Scheme.The purpose of this new teaching material, called DrModelica, is to facilitate the learning of Modelica through an environment that integrates programming, program documentation and visualization. The teaching material is intended to be used for modeling and simulation related courses at the undergraduate and graduate level.

[75] Full text  Erik Sandewall, Patrick Doherty, Oliver Lemon and Stanley Peters. 2003.
Words at the Right Time: Real-Time Dialogues with the WITAS Unmanned Aerial Vehicle.
In Proceedings of the 26th German Conference on Artificial Intelligence (KI), pages 52–63. In series: Lecture Notes in Computer Science #2821. Springer Verlag.
DOI: 10.1007/978-3-540-39451-8_5.

The WITAS project addresses the design of an intelligent, autonomous UAV (Unmanned Aerial Vehicle), in our case a helicopter. Its dialogue-system subprojects address the design of a deliberative system for natural-language and graphical dialogue with that robotic UAV. This raises new issues both for dialogue and for reasoning in real time. The following topics have been particularly important for us in various stages of the work in these subprojects: - spatiotemporal reference in the dialogue, including reference to past events and to planned or expected, future events - mixed initiative in the dialogue architecture of a complex system consisting of both dialogue-related components (speech, grammar, etc) and others (simulation, event recognition, interface to robot) and more recently as well - identification of a dialogue manager that is no more complex than what is required by the application - uniform treatment of different types of events, including the robot's own actions, observed events, communication events, and dialogue-oriented deliberation events - a logic of time, action, and spatiotemporal phenomena that facilitates the above. This paper gives a brief overview of the WITAS project as a whole, and then addresses the approaches that have been used and that are presently being considered in the work on two generations of dialogue subsystems.

[74] Andrzej Szalas. 2003.
On a logical approach to estimating computational complexity of potentially intractable problems.
In G. Goos, J. Hartmanis, and J. van Leeuwen, editors, Proceedings of the 14th International Symposium on Fundamentals of Computation Theory (FCT), pages 423–431. In series: Lecture Notes in Computer Science #2751. Springer.
DOI: 10.1007/978-3-540-45077-1_39.

In the paper we present a purely logical approach to estimating computational complexity of potentially intractable problems. The approach is based on descriptive complexity and second-order quantifier elimination techniques. We illustrate the approach on the case of the transversal hypergraph problem, TRANSHYP, which has attracted a great deal of attention. The complexity of the problem remains unsolved for over twenty years. Given two hypergraphs, G and H, TRANSHYP depends on checking whether G = H-d, where H-d is the transversal hypergraph of H. In the paper we provide a logical characterization of minimal transversals of a given hypergraph and prove that checking whether G subset of or equal to H-d is tractable. For the opposite inclusion the Problem still remains open. However, we interpret the resulting quantifier sequences in terms of determinism and bounded nondeterminism. The results give better upper bounds than those known from the literature, e.g., in the case when hypergraph H, has a sub-logarithmic number of hyperedges and (for the deterministic case) all hyperedges have the cardinality bounded by a function sub-linear wrt maximum of sizes of G and H.

[73] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2003.
On mutual understanding among communicating agents.
In B. Dunin-Keplicz and R. Verbrugge, editors, Proceedings of the International Workshop on Formal Approaches to Multi-Agent Systems (FAMAS), pages 83–97.

[72] Igor S. Pandzic, Jörgen Ahlberg, Mariusz Wzorek, Piotr Rudol and Miran Mosmondor. 2003.
Faces Everywhere: Towards Ubiquitous Production and Delivery of Face Animation.
In MUM 2003. Proceedings of the 2nd International Conference on Mobile and Ubiquitous Multimedia, 10?12 December, 2003, Norrköping, Sweden, pages 49–56. In series: Linköping Electronic Conference Proceedings #11. Linköping University Electronic Press. ISBN: 1-58113-826-1.
Link to original published article: http://www.ep.liu.se/ecp/011/010/ecp0110...
fulltext:print: http://liu.diva-portal.org/smash/get/div...

While face animation is still considered one of the toughesttasks in computer animation, its potential application range israpidly moving from the classical field of film production intogames, communications, news delivery and commerce. Tosupport such novel applications, it is important to enableproduction and delivery of face animation on a wide range ofplatforms, from high-end animation systems to the web, gameconsoles and mobile phones. Our goal is to offer a frameworkof tools interconnected by standard formats and protocols andcapable of supporting any imaginable application involvingface animation with the desired level of animation quality,automatic production wherever it is possible, and delivery ona wide range of platforms. While this is clearly an ongoingtask, we present the current state of development along withseveral case studies showing that a wide range of applicationsis already enabled.

[71] Full text  Erik Johan Sandewall. 2003.
High-level design of WWW servers in Allegro Common Lisp.
In Proceedings of the International Lisp Conference (ILC).

When invoking a function or a procedure in an ordinary programming language, it is normally assumed that the arguments may be given as composite expressions, and that they are not restricted to atomic constants or variable symbols. However, although active web pages in HTML-based web servers can be viewed as a kind of procedures, they do not enjoy the same flexibility. The present paper reports on a software package that extends the embedded web server in the ACL (Allegro Common Lisp) system and that provides it with the kind of functional flavor just described. In passing, the software also adds a number of other convenience measures to the LHTML (Lisp-encoded HTML) of the ACL server.

[70] Full text  Erik Johan Sandewall. 2003.
A software architecture for AI systems based on self-modifying software individuals.
In Proceedings of the International Lisp Conference (ILC).

The Software Individuals Architecture (SIA) is a framework fordefining software systems that are capable of self-modification and of reproductionon the level of an interpretive programming language. In abstractterms, a self-modifying system is a labelled tree containing scripts at someof its nodes; these scripts are effectively programs. A computation in sucha system executes a specific script. In doing so it maintains a local computationalstate, but it also uses and updates the labelled tree. The labelledtree, the local computational state, and the command language used for thescripts are all designed in such a way as to support self-modification andreproduction in a structured and orderly fashion.We have defined a practical system of this kind both on an abstract andformal level and as an implementation using Lisp as the host language. Thisarchitecture has been used as a platform for several applications, including inparticular the speech and natural-language dialogue system for an intelligentautonomous unmanned aerial vehicle (UAV) in the WITAS project. Thearchitecture design has been revised repeatedly as a result of using it for thisapplication as well as several others.

[69] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2003.
Tolerance Spaces and Approximative Representational Structures.
In Proceedings of the 26th German Conference on Artificial Intelligence (KI), pages 475–489. In series: Lecture Notes in Computer Science #2821. Springer.
DOI: 10.1007/978-3-540-39451-8_35.

In traditional approaches to knowledge representation, notions such as tolerance measures on data, distance between objects or individuals, and similarity measures between primitive and complex data structures are rarely considered. There is often a need to use tolerance and similarity measures in processes of data and knowledge abstraction because many complex systems which have knowledge representation components such as robots or software agents receive and process data which is incomplete, noisy, approximative and uncertain. This paper presents a framework for recursively constructing arbitrarily complex knowledge structures which may be compared for similarity, distance and approximativeness. It integrates nicely with more traditional knowledge representation techniques and attempts to bridge a gap between approximate and crisp knowledge representation. It can be viewed in part as a generalization of approximate reasoning techniques used in rough set theory. The strategy that will be used is to define tolerance and distance measures on the value sets associated with attributes or primitive data domains associated with particular applications. These tolerance and distance measures will be induced through the different levels of data and knowledge abstraction in complex representational structures. Once the tolerance and similarity measures are in place, an important structuring generalization can be made where the idea of a tolerance space is introduced. Use of these ideas is exemplified using two application domains related to sensor modeling and communication between agents.

[68] Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2003.
Information Granules for Intelligent Knowledge Structures.
In Guoyin Wang, Qing Liu, Yiyu Yao, Andrzej Skowron, editors, Proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC), pages 405–412. In series: Lecture Notes in Computer Science #2639. Springer. ISBN: 978-3-540-14040-5.
DOI: 10.1007/3-540-39205-X_68.

The premise of this paper is that the acquisition, aggregation, merging and use of information requires some new ideas, tools and techniques which can simplify the construction, analysis and use of what we call ephemeral knowledge structures. Ephemeral knowledge structures are used and constructed by granular agents. Each agent contains its own granular information structure and granular information structures of agents can be combined together. The main concept considered in this paper is an information granule. An information granule is a concise conceptual unit that can be integrated into a larger information infrastructure consisting of other information granules and dependencies between them. The novelty of this paper is that it provides a concise and formal definition of a particular view of information granule and its associated operators, as required in advanced knowledge representation applications.

[67] Full text  Patrik Haslum and Ulrich Scholz. 2003.
Domain Knowledge in Planning: Representation and Use.
In Proceedings of the ICAPS workshop on PDDL, pages 69–78.

Planning systems rely on knowledge about the problems they have to solve: The problem description and in many cases advice on how to find a solution. This paper is concerned with a third kind of knowledge which we term domain knowledge: Information about the problem that is produced by one component of the planner and used for advice by another. We first distinguish domain knowledge from the problem description and from advice, and argue for the advantages of the explict use of domain knowledge. Then we identify three classes of domain knowledge for which these advantages are most apparent and define a language, DKEL, to represent these classes. DKEL is designed as an extension to PDDL.

2002
[66] Full text  Patrik Haslum. 2002.
Partial State Progression: An Extension to the Bacchus-Kabanza Algorithm, with Applications to Prediction and MITL Consistency.
In Proceedings of the AIPS 2002 workshop on Planning via Model Checking.

[65] Full text  Jonas Kvarnström. 2002.
Applying Domain Analysis Techniques for Domain-Dependent Control in TALplanner.
In Malik Ghallab, Joachim Hertzberg, and Paolo Traverso, editors, Proceedings of the 6th International Conference on Artificial Intelligence Planning and Scheduling (AIPS). AAAI Press. ISBN: 0-57735-142-8.
DOI: 10.3233/978-1-60750-606-5-341.

A number of current planners make use of automatic domain analysis techniques to extract information such as state invariants or necessary goal orderings from a planning domain. There are also planners that allow the user to explicitly specify additional information intended to improve performance. One such planner is TALplanner, which allows the use of domain-dependent temporal control formulas for pruning a forward-chaining search tree. This leads to the question of how these two approaches can be combined. In this paper we show how to make use of automatically generated state invariants to improve the performance of testing control formulas. We also develop a new technique for analyzing control rules relative to control formulas and show how this often allows the planner to automatically strengthen the preconditions of the operators, thereby reducing time complexity and improving the performance of TALplanner by a factor of up to 400 for the largest problems from the AIPS-2000 competition.

[64] Erik Skarman and AB Saab. 2002.
EEG waves as chaotic self-oscillations.
In International Journal of Psychophysiology, pages 138–138.

[63] Full text  Erik Johan Sandewall. 2002.
Use of cognitive robotics logic in a double helix architecture for autonomous systems.
In Advances in Plan-Based Control of Robotic Agents: Revised Papers from the International Seminar at Dagstuhl Castle, pages 226–248. In series: Lecture Notes in Computer Science #2466. Springer.
DOI: 10.1007/3-540-37724-7_14.

This paper addresses the two-way relation between the architecture for cognitive robots on one hand, and a logic of action and change that is adapted to the needs of such robots on the other hand. The relation goes both ways: the logic is used within the architecture, but we also propose that an abstract model of the cognitive robot architecture shall be used for defining the semantics of the logic. For this purpose, we describe a novel architecture called the Double Helix Architecture which, unlike earlier proposals, emphasizes a precise account of the metric discrete timeline and the computational processes that take place along that timeline. The computational model of the Double Helix Architecture corresponds to the semantics of the logic being used, namely the author's Cognitive Robotics Logic which is based on the 'Features and Fluents' theory.

[62] Andrzej Szalas. 2002.
Second-order quantifier elimination in modal contexts.
In Sergio Flesca, Sergio Greco, Nicola Leone, Giovambattista Ianni, editors, Proceedings of the 8th European Conference on Logics in Artificial Intelligence (JELIA), pages 223–232. In series: Lecture Notes in Computer Science #2424. Springer. ISBN: 978-354044190-8.
DOI: 10.1007/3-540-45757-7_19.

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 generalize the result of [19] by allowing modal operators. This allows us to provide a unifying framework for many applications, that require the use of intensional concepts. Examples of applications of the technique in AI are also provided.

[61] Full text  Klas Nordberg, Patrick Doherty, Gunnar Farnebäck, Per-Erik Forssén, Gösta Granlund, Anders Moe and Johan Wiklund. 2002.
Vision for a UAV helicopter.
In International Conference on Intelligent Robots and Systems (IROS), Workshop on Aerial Robotics: Lausanne, Switzerland.

This paper presents and overview of the basic and applied research carried out by the Computer Vision Laboratory, Linköping University, in the WITAS UAV Project. This work includes customizing and redesigning vision methods to fit the particular needs and restrictions imposed by the UAV platform, e.g., for low-level vision, motion estimation, navigation, and tracking. It also includes a new learning structure for association of perception-action activations, and a runtime system for implementation and execution of vision algorithms. The paper contains also a brief introduction to the WITAS UAV Project.

[60] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2002.
CAKE: A computer aided knowledge engineering technique.
In Frank van Harmelen, editor, Proceedings of the 15th European Conference on Artificial Intelligence,2002, pages 220–224. IOS Press.

Introduction: Logic engineering often involves the development of modeling tools and inference mechanisms (both standard and non-standard) which are targeted for use in practical applications where expressiveness in representation must be traded off for efficiency in use. Some representative examples of such applications would be the structuring and querying of knowledge on the semantic web, or the representation and querying of epistemic states used with softbots, robots or smart devices. In these application areas, declarative representations of knowledge enhance the functionality of such systems and also provide a basis for insuring the pragmatic properties of modularity and incremental composition. In addition, the mechanisms developed should be tractable, but at the same time, expressive enough to represent such aspects as default reasoning, or approximate or incomplete representations of the environments in which the entities in question are embedded or used, be they virtual or actual. [...]

[59] Full text  Per Andersson, Krzysztof Kuchcinski, Klas Nordberg and Patrick Doherty. 2002.
Integrating a computational model and a run time system for image processing on a UAV.
In Euromicro Symposium on Digital System Design (DSD), pages 102–109.
DOI: 10.1109/DSD.2002.1115357.

Recently substantial research has been devoted to Unmanned Aerial Vehicles (UAVs). One of a UAV's most demanding subsystem is vision. The vision subsystem must dynamically combine different algorithms as the UAVs goal and surrounding change. To fully utilize the available hardware, a run time system must be able to vary the quality and the size of regions the algorithms are applied to, as the number of image processing tasks changes. To allow this the run time system and the underlying computational model must be integrated. In this paper we present a computational model suitable for integration with a run time system. The computational model is called Image Processing Data Flow Graph (IP-DFG). IP-DFG has been developed for modeling of complex image processing algorithms. IP-DFG is based on data flow graphs, but has been extended with hierarchy and new rules for token consumption, which makes the computational model more flexible and more suitable for human interaction. In this paper we also show that IP-DFGs are suitable for modelling expressions, including data dependent decisions and iterations, which are common in complex image processing algorithms.

2001
[58] Full text  Joakim Gustafsson. 2001.
Object-oriented Reasoning about Action and Change.
In H.H. Lund, B. Mayoh, J. Perram, editors, Proceedings of the Seventh Scandinavian Conference on Artificial Intelligence (SCAI), pages 53–64. In series: Frontiers in Artificial Intelligence and Applications #66. IOS Press. ISBN: 1-58603-161-9.

As the scope of logics of action and change continues to increase and powerful research tools are developed, it becomes possible to model larger and more complex scenarios. Unfortunately the scenarios become harder to read and difficult to modify and debug with increasing size and complexity. These problems have been overlooked in the action and change community due to the fact that only smaller toy problems are considered. Sound modeling methodology is as essential as the primitives of the modeling language. The object-oriented paradigm is one structuring mechanism that alleviates these problems and provides a systematic means of scenario construction. The topic of this paper is to demonstrate how many ideas from the object orientation paradigm can be used when reasoning about action and change, we show this by integrating the technique directly in an existing logic of action and change without any modification to the underlying logical language or semantics. 1

[57] Full text  Bourhane Kadmiry, Rainer Palm and Dimiter Driankov. 2001.
Autonomous Helicopter Control Using Gradient Descent Optimization Method.
In Proceedings of the Asian Conference on Robotic & Automation (ACRA).

The work reported in this paper is aimed at designing a velocityyaltitude and position controllers for the unmanned helicopter APID MK-III by Scandicraft AB in Sweden. The controllers are able of regulating high velocities via stabilization of the attitude angles within much larger ranges than currently available. We use a novel approach to the design consisting of two steps: rst, a gradient descent optimization method i s u s e d t o c ompute for each desired horizontal velocityyaltitude or position the corresponding desired values for the attitude angles and the main rotor col-lective pitch; second, a linear control scheme is used to regulate the attitude angles so that the helicopter achieves its desired horizontal velocity at the desired altitude, or its desired position. The performance of the controllers is evaluated in simulation and shows that the proposed design method achieves its intended purpose.

[56] Full text  Bourhane Kadmiry, Pontus Bergsten and Dimiter Driankov. 2001.
Autonomous Helicopter Control Using Fuzzy-Gain Scheduling.
In Proceedings of the IEEE International Conference on Robotic & Automation (ICRA), pages 2980–2985. IEEE. ISBN: 0-7803-6576-3.
DOI: 10.1109/ROBOT.2001.933074.

The work reported in the paper is aimed at achieving aggressive manoeuvrability for an unmanned helicopter APID MK-III by Scandicraft AB in Sweden. The manoeuvrability problem is treated at the level of attitude (pitch, roll, yaw) and the aim is to achieve stabilization of the attitude angles within much larger ranges than currently available. We present a fuzzy gain scheduling control approach based on two different types of Iinearization of the original nonlinear APID MK-III model. The performance of the fuzzy gain scheduled controllers is evaluated in simulation and shows that they are effective means for achieving the desired robust manoeuvrability.

[55] Full text  Bourhane Kadmiry and Dimiter Driankov. 2001.
Fuzzy Control of an Autonomous Helicopter.
In Proceedings of the 9th IEEE International Fuzzy Systems Association (IFSA) World Congress, pages 2797–2802. IEEE Computer Society. ISBN: 0-7803-7078-3.
DOI: 10.1109/NAFIPS.2001.943669.

This work presents a horizontal velocity controller for the unmanned helicopter APID MK-III developed by Scandicraft AB in Sweden. We use a novel approach to the design consisting of two steps: 1) Mamdani-type of fuzzy rules to compute each of the desired horizontal velocity corresponding to the desired values for the attitude angles and the main rotor collective pitch; and 2) a Takagi-Sugeno controller is used to regulate the attitude angles so that the helicopter achieves its desired horizontal velocities at a desired altitude. The performance of the combined linguistic/model-based controller is evaluated in simulation and shows that the proposed design method achieves its intended purpose

[54] Full text  Bourhane Kadmiry and Dimiter Driankov. 2001.
Autonomous Helicopter Control using Linguistic and Model-Based Fuzzy Control.
In Proceedings of the IEEE International Symposium on Intelligent Control (CCA/ISIC), pages 348–352. IEEE. ISBN: 0-7803-6722-7.
DOI: 10.1109/ISIC.2001.971534.

The paper presents the design of a horizontal velocity controller for the unmanned helicopter APID MK-III developed by Scandicraft AB in Sweden. The controller is able of regulating high horizontal velocities via stabilization of the attitude angles within much larger ranges than currently available. We use a novel approach to the design consisting of two steps: 1) a Mamdani-type of a fuzzy rules are used to compute for each desired horizontal velocity the corresponding desired values for the attitude angles and the main rotor collective pitch; and 2) using a nonlinear model of the altitude and attitude dynamics, a Takagi-Sugeno controller is used to regulate the attitude angles so that the helicopter achieves its desired horizontal velocities at a desired altitude. According to our knowledge this is the first time when a combination of linguistic and model-based fuzzy control is used for the control of a complicated plant such as an autonomous helicopter. The performance of the combined linguistic/model-based controllers is evaluated in simulation and shows that the proposed design method achieves its intended purpose

[53] Full text  Fredrik Heintz, Johan Kummeneje and Paul Scerri. 2001.
Using Simulated RoboCup to Teach AI in Undergraduate Education.
In Proceedings of the 7th Scandinavian Conference on Artificial Intelligence (SCAI), pages 13–21. In series: Frontiers in Artificial Intelligence and Applications #66. IOS Press. ISBN: 1-58603-161-9.

In this paper we argue that RoboCup is a useful tool for the teaching of AI in undergraduate education. We provide case studies, from two Swedish universities, of how RoboCup based AI courses can be implemented using a problem based approach. Although the courses were successful there are significant areas for improvement. Firstly, to help students cope with the complexity of the domain we developed RoboSoc, a general software framework for developing simulated RoboCup agents. Secondly, we propose creating close co-operation between the teachers and researchers at Scandinavian Universities with the aim of increasing the motivation of both students and teachers by providing accessible information and competence.

[52] Full text  Fredrik Heintz and Patrick Doherty. 2001.
Chronicle Recognition in the WITAS UAV Project: A Preliminary Report.
In Proceedings of the Swedish AI Society Workshop.

This paper describes the chronicle recognition problem and reports its status in the WITAS UAV project. We describe how we use the IxTeT chronicle recognition system to define chronicles (scenarios or situations), like a vehicle passing another vehicle, and how it is incorporated in the WITAS architecture. We also discuss known problems with the current system and possible directions of future research.

[51] Full text  Patrik Haslum. 2001.
Models for Prediction.
In Proceedings of the IJCAI 2001 workshop on Planning under Uncertainty and Incomplete Information (PRO-2).

Prediction is found to be a part of many more complex reasoning problems, e.g. state estimation, planning and diagnosis. In spite of this, the prediction problem is rarely studied on its own. Yet there appears to be a wide range of choices for the design of the central component in a solution to this problem, the predictive model. We examine some of the alternatives and, as a case study, present two different solutions to a specific prediction problem that we have encountered in the WITAS UAV project.

[50] Full text  Patrik Haslum and Héctor Geffner. 2001.
Heuristic Planning with Time and Resources.
In Proceedings of the 6th European Conference on Planning (ECP).

We present an algorithm for planning with time and resources based on heuristic search. The algorithm minimizes makespan using an admissible heuristic derived automatically from the problem instance. Estimators for resource consumption are derived in the same way. The goals are twofold: to show the flexibility of the heuristic search approach to planning and to develop a planner that combines expressivity and performance. Two main issues are the definition of regression in a temporal setting and the definition of the heuristic estimating completion time. A number of experiments are presented for assessing the performance of the resulting planner.

[49] Full text  Joakim Gustafsson and Jonas Kvarnström. 2001.
Elaboration Tolerance through Object-Orientation.
In Proceedings of the 5th Symposium on Logical Formalizations of Commonsense Reasoning (CommonSense).

Although many formalisms for reasoning about action and change have been proposed in the literature, their semantic adequacy has primarily been tested using tiny domains that highlight some particular aspect or problem. However, since some of the classical problems are completely or partially solved and since powerful tools are available, it is now necessary to start modeling more complex domains. This paper presents a methodology for handling such domains in a systematic manner using an object-oriented framework and provides several examples of the elaboration tolerance exhibited by the resulting models.

[48] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2001.
Computing strongest necessary and weakest sufficient conditions of first-order formulas.
In 17th International Joint Conference on Artificial Intelligence,2001, pages 145–151. Morgan Kaufmann Publishers Inc.. ISBN: 1-55860-812-5, 978-1-558-60812-2.

A technique is proposed for computing the weakest sufficient (wsc) and strongest necessary (snc) conditions for formulas in an expressive fragment of first-order logic using quantifier elimination techniques. The efficacy of the approach is demonstrated by using the techniques to compute snc's and wsc's for use in agent communication applications, theory approximation and generation of abductive hypotheses. Additionally, we generalize recent results involving the generation of successor state axioms in the propositional situation calculus via snc's to the first-order case. Subsumption results for existing approaches to this problem and a re-interpretation of the concept of forgetting as a process of quantifier elimination are also provided.

2000
[47] Jaroslaw Kachniarz and Andrzej Szalas. 2000.
Algorithms based on Symbolic Transformations of Logical Formulas in the RDL Language.
In Proceedings of the 2nd Conference on Applications of Computer Science in Mathematics and Economy, pages 101–115. WSIiE, Olsztyn, Poland.

[46] Jaroslaw Kachniarz and Andrzej Szalas. 2000.
On Rule-Based Approach to the Construction of Logical Transformers.
In Proceedings of the 1st International Workshop on Rule-Based Programming (RULE), pages 57–71. Springer Physica-Verlag.

[45] Marcus Bjäreland and George Fodor. 2000.
Execution monitoring of industrial process controllers: an application of Ontological Control.
In Prooceedings of the 4th Symposium on Fault Detection, Supervision and Safety for Technical Systems (SAFEPROCESS '00). ISBN: 0080432506.
Link: https://getinfo.de/app/Execution-Monitor...

[44] Full text  Mutsumi Nakamura, Chitta Baral and Marcus Bjäreland. 2000.
Maintainability: a weaker stabilizability-like notion for high level control of agents.
In Proceedings of the 17th National Conference on Artificial Intelligence (AAAI), pages 62–66. AAAI Press. ISBN: 978-0-262-51112-4, 978-1-57735-272-3.
Link: http://swepub.kb.se/bib/swepub:oai:DiVA....

The goal of most agents is not just to reach a goal state, but rather also (or alternatively) to put restrictions on its trajectory, in terms of states it must avoid and goals that it must ‘maintain’. This is analogous to the notions of ‘safety’ and ‘stability’ in the discrete event systems and temporal logic community. In this paper we argue that the notion of ‘stability’ is too strong for formulating ‘maintenance’ goals of an agent – in particular, reactive and software agents, and give examples of such agents. We present a weaker notion of ‘maintainability’ and show that our agents which do not satisfy the stability criteria, do satisfy the weaker criteria. We give algorithms to test maintainability, and also to generate control for maintainability. We then develop the notion of ‘supportability’ that generalizes both ‘maintainability’ and ‘stabilizability, develop an automata theory that distinguishes between exogenous and control actions, and develop a temporal logic based on it.

[43] Fredrik Heintz, Johan Kummeneje and Paul Scerri. 2000.
Simulated RoboCup in University Undergraduate Education.
In Proceedings of the Fourth Internation Workshop on RoboCup, pages 309–314. In series: Lecture Notes in Computer Science #2019. Springer Berlin/Heidelberg. ISBN: 978-3-540-42185-6, 978-3-540-45324-6.
DOI: 10.1007/3-540-45324-5_31.

We argue that RoboCup can be used to improve the teaching of AI in undergraduate education. We give some examples of how AI courses using RoboCup can be implemented using a problem based approach at two different Universities. To reduce the negative aspects found we present a solution, with the aim of easing the burden of grasping the domain of RoboCup for the students, RoboSoc which is a general framework for developing simulated RoboCup agents.

[42] Full text  Patrik Haslum and Peter Jonsson. 2000.
Planning with Reduced Operator Sets.
In Steve Chien, Subbarao Kambhampati, Craig A. Knoblock, editors, Proceedings of the 5th International Conference on Artificial Intelligence Planning and Scheduling (AIPS), pages 150–158. AAAI Press. ISBN: 978-1-57735-111-5.

Classical propositional STRIPS planning is nothing but the search for a path in the state transition graph induced by the operators in the planning problem. What makes the problem hard is the size and the sometimes adverse structure of this graph. We conjecture that the search for a plan would be more efficient if there were only a small number of paths from the initial state to the goal state. To verify this conjecture, we define the notion of reduced operator sets and describe ways of finding such reduced sets. We demonstrate that some state-of-the-art planners run faster using reduced operator sets.

[41] Full text  Patrik Haslum and Héctor Geffner. 2000.
Admissible Heuristics for Optimal Planning.
In Steve Chien, Subbarao Kambhampati, Craig A. Knoblock, editors, Proceedings of the 5th International Conference on Artificial Intelligence Planning and Scheduling (AIPS), pages 140–149. AAAI Press. ISBN: 978-1-57735-111-5.
DOI: 10.1609/aimag.v21i4.1536.
Note: There is an error in the paper: the condition for commutativity of actions (section "Commutativity Pruning") must also include that neither action adds a precondition of the other. Thus, commutativity is not the same as Graphplan-style "non-interference".
Link: http://swepub.kb.se/bib/swepub:oai:DiVA....

hsp and hspr are two recent planners that search the state-space using an heuristic function extracted from Strips encodings. hsp does a forward search from the initial state recomputing the heuristic in every state, while hspr does a regression search from the goal computing a suitable representation of the heuristic only once. Both planners have shown good performance, often producing solutions that are competitive in time and number of actions with the solutions found by Graphplan and sat planners. hsp and hsp r, however, are not optimal planners. This is because the heuristic function is not admissible and the search algorithms are not optimal. In this paper we address this problem. We formulate a new admissible heuristic for planning, use it to guide an ida search, and empirically evaluate the resulting optimal planner over a number of domains. The main contribution is the idea underlying the heuristic that yields not one but a whole family of polynomial and admissible heuristics that trade accuracy for efficiency. The formulation is general and sheds some light on the heuristics used in hsp and Graphplan, and their relation. It exploits the factored (Strips) representation of planning problems, mapping shortest-path problems in state-space into suitably defined shortest-path problems in atom-space. The formulation applies with little variation to sequential and parallel planning, and problems with different action costs.

[40] Fredrik Heintz. 2000.
FCFoo99.
In Proceedings of RoboCup-99: Robot Soccer World Cup III (RoboCup), pages 563–566. In series: Lecture Notes in Computer Science #1856. Springer London. ISBN: 3-540-41043-0.
Link: http://dl.acm.org/citation.cfm?id=698527

Introduction The emphasis of FCFoo was mainly on building a library for developers of RoboCup teams, designed especially for educational use. After the competition the library was more or less totally rewritten and nally published as part of the Master Thesis of Fredrik Heintz [4]. The agents are built on a layered reactive-deliberative architecture. The four layers describes the agent on dierent levels of abstraction and deliberation. The lowest level is mainly reactive while the others are more deliberate. The teamwork is based on nite automatas and roles. A role is a set of attributes describing some of the behaviour of a player. The decision-making uses decisiontrees to classify the situation and select the appropriate skill to perform. The other two layers are used to calculate the actual command to be sent to the server. The agent architecture and the basic design are inspired by the champions of RoboCup'98, CMUnited [6, 7]. The idea of using decision-trees and role

[39] Full text  Jonas Kvarnström, Patrick Doherty and Patrik Haslum. 2000.
Extending TALplanner with concurrency and resources.
In Proceedings of the 14th European Conference on Artificial Intelligence (ECAI), pages 501–505. In series: Frontiers in Artificial Intelligence and Applications #54. IOS Press. ISBN: 4274903885, 1586030132.
Link: http://swepub.kb.se/bib/swepub:oai:DiVA....

We present TALplanner, a forward-chaining planner based on the use of domain-dependent search control knowledge represented as temporal formulas in the Temporal Action Logic (TAL). TAL is a narrative based linear metric time logic used for reasoning about action and change in incompletely specified dynamic environments. TAL is used as the formal semantic basis for TALplanner, where a TAL goal narrative with control formulas is input to TALplanner which then generates a TAL narrative that entails the goal formula. We extend the sequential version of TALplanner, which has previously shown impressive performance on standard benchmarks, in two respects: 1) TALplanner is extended to generate concurrent plans, where operators have varied durations and internal state; and 2) the expressiveness of plan operators is extended for dealing with several different types of resources. The extensions to the planner have been implemented and concurrent planning with resources is demonstrated using an extended logistics benchmark.

[38] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 2000.
Efficient reasoning using the local closed-world assumption.
In Proceedings of the 9th International Conference on Artificial Intelligence: Methodology, Systems and Applications (AIMSA), pages 49–58. In series: Lecture Notes in Computer Science #1904. Springer Berlin/Heidelberg. ISBN: 978-3-540-41044-7, 978-3-540-45331-4.
DOI: 10.1007/3-540-45331-8_5.

We present a sound and complete, tractable inference method for reasoning with localized closed world assumptions (LCWA’s) which can be used in applications where a reasoning or planning agent can not assume complete information about planning or reasoning states. This <em>Open World Assumption</em> is generally necessary in most realistic robotics applications. The inference procedure subsumes that described in Etzioni et al [9], and others. In addition, it provides a great deal more expressivity, permitting limited use of negation and disjunction in the representation of LCWA’s, while still retaining tractability. The ap- proach is based on the use of circumscription and quantifier elimination techniques and inference is viewed as querying a deductive database. Both the preprocessing of the database using circumscription and quan- tifier elimination, and the inference method itself, have polynomial time and space complexity.

[37] Full text  Patrick Doherty, Gösta Granlund, Krzysztof Kuchcinski, Erik Johan Sandewall, Klas Nordberg, Erik Skarman and Johan Wiklund. 2000.
The WITAS unmanned aerial vehicle project.
In Werner Horn, editor, Proceedings of the 14th European Conference on Artificial Intelligence (ECAI), pages 747–755. IOS Press. ISBN: 1-58603-013-2, 4-274-90388-5.
Link: http://www2.cvl.isy.liu.se/ScOut/Publica...

The purpose of this paper is to provide a broad overview of the WITAS Unmanned Aerial Vehicle Project. The WITAS UAV project is an ambitious, long-term basic research project with the goal of developing technologies and functionalities necessary for the successful deployment of a fully autonomous UAV operating over diverse geographical terrain containing road and traffic networks. Theproject is multi-disciplinary in nature, requiring many different research competences, and covering a broad spectrum of basic research issues, many of which relate to current topics in artificial intelligence. A number of topics considered are knowledge representation issues, active vision systems and their integration with deliberative/reactive architectures, helicopter modeling and control, ground operator dialogue systems, actual physical platforms, and a number of simulation techniques.

[36] Full text  Gösta Granlund, Klas Nordberg, Johan Wiklund, Patrick Doherty, Erik Skarman and Erik Sandewall. 2000.
WITAS: An Intelligent Autonomous Aircraft Using Active Vision.
In Proceedings of the UAV 2000 International Technical Conference and Exhibition (UAV). Euro UVS.
fulltext:preprint: http://liu.diva-portal.org/smash/get/div...

The WITAS Unmanned Aerial Vehicle Project is a long term basic research project located at Linköping University (LIU), Sweden. The project is multi-disciplinary in nature and involves cooperation with different departments at LIU, and a number of other universities in Europe, the USA, and South America. In addition to academic cooperation, the project involves collaboration with a number of private companies supplying products and expertise related to simulation tools and models, and the hardware and sensory platforms used for actual flight experimentation with the UAV. Currently, the project is in its second phase with an intended duration from 2000-2003.This paper will begin with a brief overview of the project, but will focus primarily on the computer vision related issues associated with interpreting the operational environment which consists of traffic and road networks and vehicular patterns associated with these networks.

1999
[35] Andreas Nonnengart, Hans-Jürgen Ohlbach and Andrzej Szalas. 1999.
Elimination of Predicate Quantifiers.
In Logic, Language and Reasoning. Essays in Honor of Dov Gabbay, Part I, pages 159–181. Kluwer Academic Publishers.

[34] Full text  Patrik Haslum. 1999.
Model Checking by Random Walk.
In Proceedings of the ECSEL Workshop (CCSSE).

While model checking algorithms are in theory efficient, they are in practice hampered by the explosive growth of system models. We show that for certain specifications the model cheking problem reduces to a question of reachability in the system state transition graph, and apply a simple, randomized algorithm to this problem.

[33] Full text  Marcus Bjäreland and Peter Jonsson. 1999.
Exploiting bipartiteness to identify yet another tractable subclass of CSP.
In Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming (CP), pages 118–128. In series: Lecture Notes in Computer Science #1713. Springer.
DOI: 10.1007/978-3-540-48085-3_9.

The class of constraint satisfaction problems (CSPs) over finite domains has been shown to be NP-complete, but many tractable subclasses have been identified in the literature. In this paper we are interested in restrictions on the types of constraint relations in CSP instances. By a result of Jeavons et al. we know that a key to the complexity of classes arising from such restrictions is the closure properties of the sets of relations. It has been shown that sets of relations that are closed under constant, majority, affine, or associative, commutative, and idempotent (ACI) functions yield tractable subclasses of CSP. However, it has been unknown whether other closure properties may generate tractable subclasses. In this paper we introduce a class of tractable (in fact, SL-complete) CSPs based on bipartite graphs. We show that there are members of this class that are not closed under constant, majority, affine, or ACI functions, and that it, therefore, is incomparable with previously identified classes.

[32] Full text  Patrik Haslum and Peter Jonsson. 1999.
Some results on the complexity of planning with incomplete information.
In Proceedings of the 5th European Conference on Planning (ECP), pages 308–318. In series: Lecture Notes in Computer Science #1809. Springer.
DOI: 10.1007/10720246_24.

Planning with incomplete information may mean a number of different things, that certain facts of the initial state are not known, that operators can have random or nondeterministic effects, or that the plans created contain sensing operations and are branching. Study of the complexity of incomplete information planning has so far been concentrated on probabilistic domains, where a number of results have been found. We examine the complexity of planning in nondeterministic propositional domains. This differs from domains involving randomness, which has been well studied, in that for a nondeterministic choice, not even a probability distribution over the possible outcomes is known. The main result of this paper is that the non-branching plan existence problem in unobservable domains with an expressive operator formalism is EXPSPACE-complete. We also discuss several restrictions, which bring the complexity of the problem down to PSPACF-complete, and extensions to the fully and partially observable cases.

[31] Patrick Doherty, Witold Lukaszewicz and E. Madalin´ska-Bugaj. 1999.
Computing MPMA updates using dijkstra's semantics.
In 12th International Symposium on Methodologies for Intelligent Systems,1999. Springer.

[30] Full text  Patrick Doherty and Jonas Kvarnström. 1999.
TALplanner: An empirical investigation of a temporal logic-based forward chaining planner.
In Clare Dixon, Michael Fisher, editors, 6th International Workshop on Temporal Representation and Reasoning (TIME-99). IEEE Computer Society. ISBN: 0-7695-0173-7.

We present a new forward chaining planner, TALplanner, based on ideas developed by Bacchus and Kabanza, where domain-dependent search control knowledge represented as temporal formulas is used to effectively control forward chaining. Instead of using a linear modal tense logic as with Bacchus and Kabanza, we use TAL, a narrative-based linear temporal logic used for reasoning about action and change in incompletely specified dynamic environments. Two versions of TALplanner are considered, TALplan/modal which is based on the use of emulated modal formulas and a progression algorithm, and TALplan/non-modal which uses neither modal formulas nor a progression algorithm. For both versions of TALplanner and for all tested domains, TALplanner is shown to be considerably faster and requires less memory. The TAL versions also permit the representation of durative actions with internal state.

[29] John-Jules Meyer and Patrick Doherty. 1999.
Preferential action semantics (preliminary report).
In Formal Models of Agents: ESPRIT Project Modelage Final Workshop Selected Papers, pages 187–201. In series: Lecture Notes in Artificial Intelligence #1760. Springer. ISBN: 3-540-67027-0.
DOI: 10.1007/3-540-46581-2_13.
Note: Preliminary report

In this paper, we propose a new way of considering reasoning about action and change. Rather than placing a preferential structure onto the models of logical theories, we place such a structure directly on the semantics of the actions involved. In this way, we obtain a preferential semantics of actions by means of which we can not only deal with several of the traditional problems in this area such as the frame and ramification problems, but can generalize these solutions to a context which includes both nondeterministic and concurrent actions. In fact, the net result is an integration of semantical and verificational techniques from the paradigm of imperative and concurrent programs in particular, as known from traditional programming, with the AI perspective. In this paper, the main focus is on semantical (i.e. model theoretical) issues rather than providing a logical calculus, which would be the next step in the endeavor.

[28] Full text  Silvia Coradeschi, Lars Karlsson and Klas Nordberg. 1999.
Integration of vision and decision-making in an autonomous airborne vehicle for traffic surveillance.
In Proceedings of the International Conference on Vision Systems '99: Grand Canary.

In this paper we present a system which integrates computer vision and decision-making in an autonomous airborne vehicle that performs traffic surveillance tasks. The main factors that make the integration of vision and decision-making a challenging problem are: the qualitatively different kind of information at the decision-making and vision levels, the need for integration of dynamically acquired information with a priori knowledge, e.g. GIS information, and the need of close feedback and guidance of the vision module by the decision-making module. Given the complex interaction between the vision module and the decision-making module we propose the adoption of an intermediate structure, called Scene Information Manager, and describe its structure and functionalities.

1998
[27] Måns Engman, Tommy Persson and Peter Fritzson. 1998.
Generating Parallel Graphics Code from Symbolic-algebra Specifications.
In .

[26] Lars Karlsson, Joakim Gustafsson and Patrick Doherty. 1998.
Delayed effects of actions.
In Proceedings of the 13th European Conference on Artificial Intelligence (ECAI), pages 542–546. John Wiley & Sons. ISBN: 978-0471984313.

[25] Full text  Patrick Doherty, Witold Lukaszewicz and Ewa Madalinska-Bugaj. 1998.
The PMA and relativizing change for action update.
In Proceedings of the 6th International Conference on Principles of Knowledge Representation and Reasoning (KR), pages 258–269. Morgan Kaufmann Publishers.

Using intuitions from the temporal reasoning community, we provide a generalization of the PMA, called the modified PMA (MPMA), which permits the representation of disjunctive updates and the use of integrity constraints interpreted as causal constraints. In addition, we provide a number of syntactic characterizations of the MPMA, one of which is constructed by mapping an MPMA update of a knowledge base into a temporal narrative in a simple temporal logic (STL). The resulting representation theorem provides a basis for computing entailments of the MPMA and could serve as a basis for further generalization of the belief update approach for reasoning about action and change.

[24] Full text  Patrick Doherty and Jonas Kvarnström. 1998.
Tackling the qualification problem using fluent dependency constraints.
In Lina Khatib, Robert Morris, editors, Proceedings of the 5th International Workshop on Temporal Representation and Reasoning (TIME-98). IEEE Computer Society. ISBN: 0-8186-8473-9.
Note: Preliminary report

The use of causal rules or fluent dependency constraints has proven to provide a versatile means of dealing with the ramification problem. In this paper we show how fluent dependency constraints together with the use of durational fluents can be used to deal with problems associated with action qualification. We provide both a \emph{weak} and \emph{strong} form of qualification and demonstrate the approach using an action scenario which combines solutions to the frame, ramification and qualification problems in the context of actions with duration, concurrent actions, non-deterministic actions and the use of both boolean and non-boolean fluents. The circumscription policy used for the combined problems is reducible to the 1st-order case. In addition, we demonstrate the use of a research tool VITAL, for querying and visualizing action scenarios.

1997
[23] Full text  Thomas Drakengren and Marcus Bjäreland. 1997.
Reasoning about Action in Polynomial Time.
In Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI).

[22] Full text  Marcus Bjäreland and Lars Karlsson. 1997.
Reasoning by Regression: Pre- and Postdiction Procedures for Logics of Action and Change with Nondeterminism.
In Proceedings of the 15th International Joint Conference on Artficial Intelligence (IJCAI).

[21] Silvia Coradeschi, Klas Nordberg and Lars Karlsson. 1997.
Integration of vision and reasoning in an airborne autonomous vehicle for traffic surveillance.
In Knowledge Based Computer Vision, Seminar-Report 196: Schloss Dagstuhl, Germany.

1996
[20] Tommy Persson and Peter Fritzson. 1996.
Parallel implementation of image reconstruction for the CARABAS long-wave penetrating radar.
In Heather Liddel, lAdrian Colbrook, Bob Hertzberger, Peter Sloot, editors, High-Performance Computing and Networking, pages 327–332. In series: Lecture Notes in Computer Science #1067. Springer Berlin/Heidelberg. ISBN: 978-3-540-61142-4, 978-3-540-49955-8.
DOI: 10.1007/3-540-61142-8_566.
Fulltext: https://doi.org/10.1007/3-540-61142-8_56...

CARABAS (Coherent All RAdio BAnd Sensing) is a new type of radar that has the unique property of being able to penetrate through vegetation, and to some extent into upper levels of soil depending on water content. This can be done by using long radar waves in the range 3–15 meters, and new algorithms for image reconstruction from information in reflected radar waves. These algorithms are related to methods used for computer tomography, and are very computationally expensive. Two classes of algorithms for image reconstruction are direct Fourier methods and filtered backprojection. Even though filtered backprojection is more computationally demanding, we chose that method since it is easier to parallelize, it has better real-time properties, and it is easier to compensate for disturbances and achieve good image quality.In this paper we report results from the first parallel implementation of the CARABAS algorithms. The benchmarking was done on a Parsytec PowerGC MIMD computer with 128 PowerPC 601 processors. We come close to achieving the real-time requirement for significant parts of the computation.

[19] Full text  Joakim Gustafsson and Patrick Doherty. 1996.
Embracing occlusion in specifying the indirect effects of actions.
In Luigia Carlucci Aiello, Jon Doyle, Stuart C. Shapiro, editors, Proceedings of the 5th International Conference on Principles of Knowledge Representation and Reasoning, pages 87–98. Morgan Kaufmann Publishers. ISBN: 1-55860-421-9.

In this paper, we extend PMON, a logic for reasoning about action and change, with causal rules which are used to specify the indirect effects of actions The extension, called PMON(RCs), has the advantage of using explicit time, includes actions with durations, nondeterministic actions, allows partial specification of the timing and order of actions and has been assessed correct for at least the K-IA class of action scenarios within the Features and Fluents framework Most importantly, the circumscription policy used is easily shown to be reducible to the firstorder case which insures that standard theorem proving techniques and their optimizations may be used to compute entailment In addition, we show how the occlusion concept previously used to deal with duration and nondeterministic actions proves to be equally versatile in representing causal constraints and delayed effects of actions We also discuss related work and consider the strong correspondence between our work and recent work by Lin, who uses a Cause predicate to specify indirect effects similar to our use of Occlude in PMON, and a minimization policy related to that used in PMON.

[18] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 1996.
Explaining explanation closure.
In Zbigniew W. Ras, Maciek Michalewicz, editors, Proceedings of the 9th International Symposium on Methodologies for Intelligent Systems,1996, pages 521–530. In series: Lecture Notes in Computer Science #1079. Springer Berlin/Heidelberg. ISBN: 3-540-61286-6.
DOI: 10.1007/3-540-61286-6_176.

Recently, Haas, Schubert, and Reiter, have developed an alternative approach to the frame problem which is based on the idea of using <em>explanation closure axioms</em>. The claim is that there is a monotonic solution for characterizing nonchange in serial worlds with fully specified actions, where one can have both a succinct representation of frame axioms and an effective proof theory for the characterization. In the paper, we propose a circumscriptive version of explanation closure, PMON, that has an effective proof theory and works for both context dependent and nondeterministic actions. The approach retains representational succinctness and a large degree of elaboration tolerance, since the process of generating closure axioms is fully automated and is of no concern to the knowledge engineer. In addition, we argue that the monotonic/nonmonotonic dichotomy proposed by others is not as sharp as previously claimed and is not fully justified.

[17] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 1996.
General domain circumscription and its first-order reduction.
In Dov Gabbay, Hans Olbach, editors, Proceedings of the 1st International Conference on Formal and Applied Practical Reasoning (FAPR), pages 93–109. In series: Lecture Notes in Computer Science #1085. Springer Berlin/Heidelberg. ISBN: 978-3-540-61313-8.
DOI: 10.1007/3-540-61313-7_65.

We first define general domain circumscription (GDC) and provide it with a semantics. GDC subsumes existing domain circumscription proposals in that it allows varying of arbitrary predicates, functions, or constants, to maximize the minimization of the domain of a theory We then show that for the class of semi-universal theories without function symbols, that the domain circumscription of such theories can be constructively reduced to logically equivalent first-order theories by using an extension of the DLS algorithm, previously proposed by the authors for reducing second-order formulas. We also isolate a class of domain circumscribed theories, such that any arbitrary second-order circumscription policy applied to these theories is guaranteed to be reducible to a logically equivalent first-order theory. In the case of semi-universal theories with functions and arbitrary theories which are not separated, we provide additional results, which although not guaranteed to provide reductions in all cases, do provide reductions in some cases. These results are based on the use of fixpoint reductions.

1995
[16] Full text  Patrick Doherty, Witold Lukaszewicz and Andrzej Szalas. 1995.
Computing circumscription revisited.
In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI), pages 1502–1508. ISBN: 978-1558603639.
Note: Volume 2. Preliminary report

[15] Patrick Doherty and P. Peppas. 1995.
A comparison between two approaches to ramification: PMON(R) and AR0.
In 8th Australian Joint Conference on Artificial Intelligence,1995.
Note: World Scientific

1994
[14] Andrzej Szalas. 1994.
Genetic Algorithms for Decision Problems.
In Proceedings of the 6th International Conference on Artificial Intelligence and Information-Control Systems of Robots (AIICSR), pages 383–390. World Scientific. ISBN: 981-02-1877-X.

[13] Patrick Doherty and Witold Lukaszewicz. 1994.
Circumscribing features and fluents. A fluent logic for reasoning about action and change.
In 8th International Symposium on Methodologies for Intelligent Systems,1994. Springer Verlag.

[12] Patrick Doherty. 1994.
Reasoning about action and change using occlusion.
In 11th European Conference on Artificial Intelligence,1994. John Wiley and Sons.

1992
[11] Patrick Doherty and Witold Lukaszewicz. 1992.
Defaults as first-class citizens.
In Proceedings of the 22nd International Symposium on Multiple-Valued Logic (SMVL), pages 146–154. In series: Proceedings of the International Symposium on Multiple Valued Logic #??. IEEE Computer Society. ISBN: 0-8186-2680-1.

A nonmonotonic logic with explicit defaults, NML3, is presented. It is characterized by the following features: (1) the use of the strong Kleene three-valued logic as a basis; (2) the addition of an explicit default operator which enables distinguishing tentative conclusions from ordinary conclusions in the object language; and (3) the use of the idea of preferential entailment to generate nonmonotonic behavior. The central feature of the formalism, the use of an explicit default operator with a model-theoretic semantics based on the notion of a partial interpretation, distinguishes NML3 from most previous formalisms. By capitalizing on the distinction between tentative and ordinary conclusions, NML3 provides increased expressibility in comparison to many of the standard nonmonotonic formalisms and greater flexibility in the representation of subtle aspects of default reasoning. This is shown through examples.

[10] Patrick Doherty and Witold Lukaszewicz. 1992.
FONML3 - A first-order non-monotonic logic with explicit defaults.
In European Conference on Artificial Intelligence, ECAI-92,1992. John Wiley and Sons.

[9] Patrick Doherty, Dimiter Driankov and H. Hellendoorn. 1992.
Fuzzy if-then-unless rules and their implementation.
In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU92,1992. Springer.

[8] Patrick Doherty, Dimiter Driankov and A. Tsoukias. 1992.
Partial logics and partial preferences.
In International Conference on Economics/Management and Information Technology,1992.

1991
[7] Patrick Doherty and Dimiter Driankov. 1991.
A non-monotonic fuzzy logic.
In International Fuzzy Systems Association, Fourth World Congress,1991.

[6] Patrick Doherty. 1991.
A constraint-based approach to proof procedures for multi-valued logics.
In Proceedings of the 1st World Conference on Fundamentals of Artificial Intelligence (WOCFAI). Springer.

1990
[5] Patrick Doherty. 1990.
NME - A three-valued non-monotonic formalism.
In Proceedings of the 5th International Symposium on Methodologies for Intelligent Systems (ISMIS).
Note: Preliminary report

[4] Patrick Doherty. 1990.
NM3 - A three-valued cumulative non-monotonic formalism.
In Jan van Eijck, editor, Logics in AI, European Workshop (JELIA), pages 196–211. In series: Lecture Notes in Artificial Intelligence #478. Springer Berlin/Heidelberg. ISBN: 978-3-540-53686-4.
DOI: 10.1007/BFb0018442.

In this paper, we propose a formalization of non-monotonic reasoning using a three-valued logic based on the strong definitions of Kleene. We start by extending Kleene's three-valued logic with an \"external negation\" connective where ~ alpha is true when alpha is false or unknown. In addition, a default operator D is added where D alpha is interpreted as \"alpha is true by default\". The addition of the default operator increases the expressivity of the language, where statements such as \"alpha is not a default\" are directly representable. The logic has an intuitive model theoretic semantics without any appeal to the use of a fixpoint semantics for the default operator. The semantics is based on the notion of preferential entailment, where a set of sentences Gamma preferentially entails a sentence alpha, if and only if a preferred set of the models of Gamma are models of alpha. We also show that the logic belongs to the class of cumulative non-monotonic formalisms which are a subject of current interest.

1989
[3] Patrick Doherty. 1989.
A correspondence between inheritance hierarchies and a logic of preferential entailment.
In M. L. Emrich, M. S. Pfeifer, M. Hadzikadic, and Z. W. Ras, editors, Proceedings of the 4th International Symposium on Methodologies for Intelligent Systems (ISMIS). University of North Carolina Press.

[2] Patrick Doherty. 1989.
A semantics for inheritance hierarchies with exceptions using a logic of preferential entailment.
In Proceedings of the 2nd Scandinavian Conference on Artificial Intelligence (SCAI). IOS Press.

1987
[1] R. J. Cunningham, Andreas Nonnengart and Andrzej Szalas. 1987.
A Compositional Method for the Design and Proof of Asynchronous Processes.
In Proceedings of the 4th Annual ESPRIT Conference (ESPRIT), pages 566–580. North-Holland. ISBN: 0-444-70333-0.


Page responsible: Patrick Doherty
Last updated: 2014-04-30