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

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

[28] Linh Anh Nguyen and Andrzej Szalas. 2013.
Logic-Based Roughification.
In A. Skowron and Z. Suraj, editors, Rough Sets and Intelligent Systems - Professor Zdzis?aw Pawlak in Memoriam (vol. I), pages 517–543. In series: Intelligent Systems Reference Library #42. Springer Berlin/Heidelberg. ISBN: 978-3-642-30343-2.
DOI: 10.1007/978-3-642-30344-9_19.

The current chapter is devoted to <em>roughification</em>. In the most general setting, we intend the term <em>roughification</em> to refer to methods/techniques of constructing equivalence/similarity relations adequate for Pawlak-like approximations. Such techniques are fundamental in rough set theory. We propose and investigate novel roughification techniques. We show that using the proposed techniques one can often discern objects indiscernible by original similarity relations, what results in improving approximations. We also discuss applications of the proposed techniques in granulating relational databases and concept learning. The last application is particularly interesting, as it shows an approach to concept learning which is more general than approaches based solely on information and decision systems.

[27] 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.
DOI: 10.1007/978-3-642-32524-3_9.
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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
[26] Patrick Doherty and John-Jules Ch. Meyer. 2012.
On the Logic of Delegation - Relating Theory and Practice.
In Fabio Paglieri, Luca Tummolini, Rino Falcone, Maria Miceli, editors, The Goals of Cognition: Essays in honour of Cristiano Castelfranchi, pages 467–496. College Publications. ISBN: 978-1848900943.
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Research with collaborative robotic systems has much to gain by leveraging concepts and ideas from the areas of multi-agent systems and the social sciences. In this paper we propose an approach to formalizing and grounding important aspects of collaboration in a collaborative system shell for robotic systems. This is done primarily in terms of the concept of delegation, where delegation will be instantiated as a speech act. The formal characterization of the delegation speech act is based on a preformal theory of delegation proposed by Falcone and Castelfranchi. We show how the delegation speech act can in fact be used to formally ground an abstract characterization of delegation into a FIPA-compliant implementation in an agent-oriented language such as JADE, as part of a collaborative system shell for robotic systems. The collaborative system shell has been developed as a prototype and used in collaborative missions with multiple unmanned aerial vehicle systems.

[25] Full text  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, e-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.

[24] Full text  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, e-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.

[23] Barbara Dunin-Keplicz and Andrzej Szalas. 2012.
Epistemic Profiles and Belief Structures.
In Gordan Jezic , Mario Kusek , Ngoc-Thanh Nguyen , Robert J. Howlett and 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, e- 978-3-642-30947-2.
DOI: 10.1007/978-3-642-30947-2_40.

The paper is devoted to a novel formalization of beliefs in multiagent systems. Our aim is to bridge the gap between idealized logical approaches to modeling beliefs and their actual implementations. Therefore the stages of belief acquisition, intermediate reasoning and final belief formation are isolated and analyzed. We give a novel semantics reflecting those stages and suitable for building complex belief structures in the context of incomplete and/or inconsistent information. Namely, an agent starts with constituents, i.e., sets of initial beliefs acquired by perception, expert supplied knowledge, communication with other agents and perhaps other ways. Next, the constituents are transformed into consequents according to agents’ epistemic profiles. Additionally, a uniform treatment of single agent and group beliefs is achieved. Importantly, we indicate an implementation framework ensuring tractability of reasoning about beliefs.

[22] Linh Anh Nguyen and Andrzej Szalas. 2012.
Paraconsistent Reasoning for Semantic Web Agents.
In Ngoc Thanh Nguyen, editor, Transactions on Compuational Collective Intelligence VI, pages 36–55. In series: Lecture Notes in Computer Science #7190. Springer Berlin/Heidelberg. ISBN: 978-3-642-29355-9, e-978-3-642-29356-6.
DOI: 10.1007/978-3-642-29356-6_2.

Description logics 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. Among them, one of the most important logics is <em>SROIQ</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/char52.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char4F.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\" />, providing the logical foundation for the OWL 2 Web Ontology Language recommended by W3C in October 2009. 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 introduce a number of paraconsistent semantics for <em>SROIQ</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/char52.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char4F.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\" />, including three-valued and four-valued semantics. The four-valued semantics reflects the well-known approach introduced in [5,4] and is considered here for comparison reasons only. We also study the relationship between the semantics and paraconsistent reasoning in <em>SROIQ</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/char52.png\" /><img src=\"http://www.springerlink.com/jsMath/fonts/cmsy10/alpha/120/char4F.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\" /> through a translation into the traditional two-valued semantics. Such a translation allows one to use existing tools and reasoners to deal with inconsistent knowledge.

[21] Barbara Dunin-Keplicz and Andrzej Szalas. 2012.
Agents in Approximate Environments.
In Jan Ejick and Rineke Verbrugge, editors, Games, Actions and Social Software: Multidisciplinary Aspects, pages 141–163. In series: Lecture Notes in Computer Science #7010. Springer. ISBN: 978-3-642-29325-2 (print), 978-3-642-29326-9 (online).
DOI: 10.1007/978-3-642-29326-9_8.

The starting point of this research is the multimodal approach to modeling multiagent systems, especially Beliefs, Goals and Intention systems. Such an approach is suitable for specifying and verifying many subtle aspects of agents’ informational and motivational attitudes.However, in this chapter we make a shift in a perspective. More precisely, we propose the method of embedding multimodal approaches into a form of approximate reasoning suitable for modeling perception, namely a <em>similarity-based approximate reasoning</em>. We argue that this formalism allows one to both keep the intuitive semantics compatible with that of multimodal logics as well as to model and implement phenomena occurring at the perception level.

2011
[20] Full text  Patrick Doherty, Fredrik Heintz and David Landén. 2011.
A Delegation-Based Architecture for Collaborative Robotics.
In Danny Weyns and Marie-Pierre Gleizes, editors, Agent-Oriented Software Engineering XI: 11th International Workshop, AOSE 2010, Toronto, Canada, May 10-11, 2010, Revised Selected Papers, pages 205–247. In series: Lecture Notes in Computer Science #6788. Springer Berlin/Heidelberg. ISBN: 978-3-642-22635-9.
DOI: 10.1007/978-3-642-22636-6_13.
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Collaborative robotic systems have much to gain by leveraging results from the area of multi-agent systems and in particular agent-oriented software engineering. Agent-oriented software engineering has much to gain by using collaborative robotic systems as a testbed. In this article, we propose and specify a formally grounded generic collaborative system shell for robotic systems and human operated ground control systems. Collaboration is formalized in terms of the concept of delegation and delegation is instantiated as a speech act. Task Specification Trees are introduced as both a formal and pragmatic characterization of tasks and tasks are recursively delegated through a delegation process implemented in the collaborative system shell. The delegation speech act is formally grounded in the implementation using Task Specification Trees, task allocation via auctions and distributed constraint problem solving. The system is implemented as a prototype on Unmanned Aerial Vehicle systems and a case study targeting emergency service applications is presented.

2009
[19] Full text  Patrick Doherty and Jonas Kvarnström. 2009.
Temporal Action Logics.
In V. Lifschitz, F. van Harmelen, and F. Porter, editors, Handbook of Knowledge Representation, pages 709–757. In series: Foundations of Artificial Intelligence #3. Elsevier. ISBN: 978-0-444-52211-5.
DOI: 10.1016/S1574-6526(07)03018-0.
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The study of frameworks and formalisms for reasoning about action and change [67, 58, 61, 65, 70, 3, 57] has been central to the knowledge representation field almost from the inception of Artificial Intelligence as a general field of research [52, 56]. The phrase “Temporal Action Logics” represents a class of logics for reasoning about action and change that evolved from Sandewall’s book on Features and Fluents [61] and owes much to this ambitious project. There are essentially three major parts to Sandewall’s work. He first developed a narrative-based logical framework for specifying agent behavior in terms of action scenarios. The logical framework is state-based and uses explicit time structures. He then developed a formal framework for assessing the correctness (soundness and completeness) of logics for reasoning about action and change relative to a set of well-defined intended conclusions, where reasoning problems were classified according to their ontological or epistemological characteristics. Finally, he proposed a number of logics defined semantically in terms of definitions of preferential entailment1 and assessed their correctness using his assessment framework.

[18] Andrzej Szalas and Alicja Szalas. 2009.
Paraconsistent Reasoning with Words.
In Aspects of Natural Language Processing: Essays Dedicated to Leonard Bolc on the Occasion of His 75th Birthday, pages 43–58. In series: Lecture Notes in Computer Science #5070. Springer. ISBN: 978-3-642-04734-3.
DOI: 10.1007/978-3-642-04735-0_2.
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Fuzzy logics are one of the most frequent approaches to model uncertainty and vagueness. In the case of fuzzy modeling, degrees of belief and disbelief sum up to 1, which causes problems in modeling the lack of knowledge and inconsistency. Therefore, so called paraconsistent intuitionistic fuzzy sets have been introduced, where the degrees of belief and disbelief are not required to sum up to 1. The situation when this sum is smaller than 1 reflects the lack of knowledge and its value greater than 1 models inconsistency. In many applications there is a strong need to guide and interpret fuzzy-like reasoning using qualitative approaches. To achieve this goal in the presence of uncertainty, lack of knowledge and inconsistency, we provide a framework for qualitative interpretation of the results of fuzzy-like reasoning by labeling numbers with words, like <em>true, false, inconsistent, unknown</em>, reflecting truth values of a suitable, usually finitely valued logical formalism.

2008
[17] Erik Sandewall. 2008.
The Leordo Computation System.
In Yves Bertot, GĂ©rard Huet, Jean-Jacques LĂ©vy, Gordon Plotkin., editors, From Semantics to Computer Science: Essays in Honour of Gilles Kahn, pages 309–336. Cambridge University Press. ISBN: 978-05-21-51825-3, 978-05-11-77052-4.
DOI: 10.1017/CBO9780511770524.015.
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Gilles Kahn was one of the most influential figures in the development of computer science and information technology, not only in Europe but throughout the world. This volume of articles by several leading computer scientists serves as a fitting memorial to Kahn's achievements and reflects the broad range of subjects to which he contributed through his scientific research and his work at INRIA, the French National Institute for Research in Computer Science and Control. The editors also reflect upon the future of computing: how it will develop as a subject in itself and how it will affect other disciplines, from biology and medical informatics, to web and networks in general. Its breadth of coverage, topicality, originality and depth of contribution, make this book a stimulating read for all those interested in the future development of information technology.

[16] Per-Magnus Olsson. 2008.
Practical Pathfinding in Dynamic Environments.
In Steve Rabin, editor, AI Game Programming Wisdom 4. Charles River. ISBN: 978-1-58450-523-5, 158-450-523-0.
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link: http://www.amazon.com/AI-Game-Programmin...

Welcome to the latest volume of AI Game Programming Wisdom! AI Game Programming Wisdom 4 includes a collection of more than 50 new articles featuring cutting-edge techniques, algorithms, and architectures written by industry professionals for use in commercial game development. Organized into 7 sections, this comprehensive volume explores every important aspect of AI programming to help you develop and expand your own personal AI toolbox. You'll find ready-to-use ideas, algorithms, and code in all key AI areas including general wisdom, scripting and dialogue, movement and pathfinding, architecture, tactics and planning, genre specific, and learning and adaptation. New to this volume are articles on recent advances in realistic agent, squad, and vehicle movement, as well as dynamically changing terrain, as exemplified in such popular games as Company of Heroes.You'll also find information on planning as a key game architecture, as well as important new advances in learning algorithms and player modeling. AI Game Programming Wisdom 4 features coverage of multiprocessor architectures, Bayesian networks, planning architectures, conversational AI, reinforcement learning, and player modeling.These valuable and innovative insights and issues offer the possibility of new game AI experiences and will undoubtedly contribute to taking the games of tomorrow to the next level.

2007
[15] Jan Maluszynski, Andrzej Szalas and Aida Vitoria. 2007.
A Four-Valued Logic for Rough Set-Like Approximate Reasoning.
In James F. Peters, Andrzej Skowron, Ivo DĂĽntsch, Jerzy Grzymala-Busse, Ewa Orlowska and Lech Polkowski, editors, Transactions on Rough Sets VI, pages 176–190. In series: Lecture Notes in Computer Science #4374/2007. Springer. ISBN: 3-540-71198-8, 978-3-540-71198-8.
DOI: 10.1007/978-3-540-71200-8_11.
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Annotation The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume VI of the Transactions on Rough Sets (TRS) commemorates the life and work of Zdzislaw Pawlak (1926-2006). His legacy is rich and varied. Prof. Pawlak's research contributions have had far-reaching implications inasmuch as his works are fundamental in establishing new perspectives for scientific research in a wide spectrum of fields. This volume of the TRS presents papers that reflect the profound influence of a number of research initiatives by Professor Pawlak. In particular, this volume introduces a number of new advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science. These advances have significant implications in a number of research areas such as the foundations of rough sets, approximate reasoning, bioinformatics, computational intelligence, cognitive science, data mining, information systems, intelligent systems, machine intelligence, and security.

2006
[14] Full text  Erik Johan Sandewall. 2006.
Coordination of actions in an autonomous robotic system.
In Oliviero Stock, Marco Schaerf, editors, Reasoning, Action and Interaction in AI Theories and Systems: Essays Dedicated to Luigia Carlucci Aiello, pages 177–191. In series: Lecture Notes in Computer Science #4155. Springer. ISBN: 978-3-5403-7901-0, 978-3-5403-7902-7.
DOI: 10.1007/11829263_10.
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link: http://www.amazon.com/Reasoning-Action-I...

The present book is a festschrift in honor of Luigia Carlucci Aiello. The 18 articles included are written by former students, friends, and international colleagues, who have cooperated with Luigia Carlucci Aiello, scientifically or in AI boards or committees. The contributions by reputed researchers span a wide range of AI topics and reflect the breadth and depth of Aiello's own work

2004
[13] Patrick Doherty, Jaroslaw Kachniarz and Andrzej Szalas. 2004.
Using Contextually Closed Queries for Local Closed-World Reasoning in Rough Knowledge Databases.
In Andrzej Skowron,Lech Polkowski ,Sankar K Pal, editors, Rough-Neural Computing: Techniques for Computing with Words, pages 219–250. In series: Cognitive Technologies #??. Springer. ISBN: 978-3-540-43059-9, 35-4043-059-8.
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Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g., in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, and genetic algorithms.It is well understood now in the soft computing community that hybrid approaches combining various paradigms provide very promising attempts to solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neurocomputing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

[12] Patrick Doherty, Witold Lukaszewicz, Andrzej Skowron and Andrzej Szalas. 2004.
Approximation Transducers and Trees: A Technique for Combining Rough and Crisp Knowledge.
In Andrzej Skowron,Lech Polkowski ,Sankar K Pal, editors, Rough-Neural Computing: Techniques for Computing with Words, pages 189–218. In series: Cognitive Technologies #??. Springer. ISBN: 978-3-540-43059-9, 35-4043-059-8.
find book at a swedish library/hitta boken i ett svenskt bibliotek: http://libris.kb.se/bib/14144444
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Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g., in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, and genetic algorithms.It is well understood now in the soft computing community that hybrid approaches combining various paradigms provide very promising attempts to solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neurocomputing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

2002
[11] John-Jules Meyer and Patrick Doherty. 2002.
Preferential Action Semantics.
In John-Jules Ch Meyer; Jan Treur, editor, Handbook of Defeasible Reasoning and Uncertainty Management Systems: Volume 7:: Agent-Based Defeasible Control in Dynamic Environments. In series: Handbook of Defeasible Reasoning and Uncertainty Management Systems #7. Kluwer. ISBN: 978-1-4020-0834-4, 14-02-0-0834-1.
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This last volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems is - together with Volume 6 - devoted to the topics Reasoning and Dynamics, covering both the topics of \"Dynamics of Reasoning,\" where reasoning is viewed as a process, and \"Reasoning about Dynamics,\" which must be understood as pertaining to how both designers of, and agents within dynamic systems may reason about these systems. The present volume presents work done in this context and is more focused on \"reasoning about dynamics,\" viz. how (human and artificial) agents reason about (systems in) dynamic environments in order to control them. In particular modelling frameworks and generic agent models for modelling these dynamic systems and formal approaches to these systems such as logics for agents and formal means to reason about agent-based and compositional systems, and action &amp; change more in general are considered.

2001
[10] Jaroslaw Kachniarz and Andrzej Szalas. 2001.
On a Static Approach to Verification of Integrity Constraints in Relational Databases.
In Eva Orlowska, Andrzej Szalas, editors, Relational Methods for Computer Science Applications, pages 97–109. In series: Studies in Fuzziness and Soft Computing #65. Springer Physica-Verlag. ISBN: 3-7908-1365-6.
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1999
[9] Paul Scerri, Silvia Coradeschi and Anders Törne. 1999.
A user oriented system for developing behavior based agents.
In Minoru Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer World Cup II, pages 173–186. In series: Lecture Notes in Computer Science #1604. Springer Berlin/Heidelberg. ISBN: 978-3-540-66320-1, e-978-3-540-48422-6, 3-540-66320-7.
DOI: 10.1007/3-540-48422-1_14.

Developing agents for simulation environments is usually the responsibility of computer experts. However, as domain experts have superior knowledge of the intended agent behavior, it is desirable to have domain experts directly specifying behavior. In this paper we describe a system which allows non-computer experts to specify the behavior of agents for the RoboCup domain. An agent designer is presented with a Graphical User Interface with which he can specify behaviors and activation conditions for behaviors in a layered behavior-based system. To support the testing and debugging process we are also developing interfaces that show, in real-time, the world from the agents perspective and the state of its reasoning process.

[8] Silvia Coradeschi and Jasec Malec. 1999.
How to make a challenging AI course enjoyable using the RoboCup soccer simulation system.
In Minoru Asada and Hiroaki Kitano, editors, RoboCup-98: Robot Soccer World Cup II, pages 120–124. In series: Lecture Notes in Computer Science #1604. Springer Berlin/Heidelberg. ISBN: 3-540-66320-7.
DOI: 10.1007/3-540-48422-1_9.

In this paper we present an AI programming organised around the RoboCup soccer simulation system. The course participants create a number of software agents that form a team, and participate in a tournament at the end of the course. The use of a challenging and interesting task, and the incentive of having a tournament has made the course quite successful, both in term of enthusiasm of the students and of knowledge acquired. In the paper we describe the structure of the course, discuss in what respect we think the course has met its aim, and the opinions of the students about the course.

1998
[7] Andreas Nonnengart and Andrzej Szalas. 1998.
A Fixpoint Approach to Second-Order Quantifier Elimination with Applications to Correspondence Theory.
In Ewa Orlowska, editor, Logic at work: essays dedicated to the memory of Helena Rasiowa, pages 307–328. In series: Studies in Fuzziness and Soft Computing #24. Physica Verlag. ISBN: 3-7908-1164-5.
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1996
[6] Patrick Doherty and Witold Lukaszewicz. 1996.
A study in modal embeddings of NML3.
In Patrick Doherty, editor, Partiality, Modality, and Nonmonotonicity, Studies in Logic, Language and Information., pages 145–168. CSLI Publications. ISBN: 1-57586-031-7 (inb.), 1-57586-030-9 (hft.).

1995
[5] Andrzej Szalas. 1995.
Temporal Logic: A Standard Approach.
In Leonard Bolc, Andrzej Szalas, editors, Time And Logic: A Computational Approach, pages 1–50. UCL Press Ltd.. ISBN: 1-85728-233-7, 978-1857282337.
Find book at a Swedish library/Hitta boken i ett svenskt bibliotek: http://libris.kb.se/hitlist?d=libris&q=1...
Find book in another country/Hitta boken i ett annat land: http://www.worldcat.org/search?q=978-185...

1994
[4] Patrick Doherty and Witold Lukaszewicz. 1994.
Circumscribing features and fluents.
In Dov M. Gabbay and Hans JĂĽrgen Ohlbach, editors, Temporal Logic: First International Conference, ICTL'94 Bonn, Germany, July 11?14, 1994 Proceedings, pages 82–100. In series: Lecture Notes in Computer Science #827. Springer Berlin/Heidelberg. ISBN: 3-540-58241-X (Berlin), 0-387-58241-X (New York).
DOI: 10.1007/BFb0013982.

Sandewall has recently proposed a systematic approach to the representation of knowledge about dynamical systems that includes a general framework in which to assess the range of applicability of existing and new logics for action and change and to provide a means of studying whether and in what sense the logics of action and change are relevant for intelligent agents. As part of the framework, a number of logics of preferential entailment are introduced and assessed for particular classes of action scenario descriptions. This paper provides syntactic characterizations of several of these relations of preferential entailment in terms of standard FOPC and circumscription axioms. The intent is to simplify the process of comparison with existing formalisms which use more traditional techniques and to provide a basis for studying the feasibility of compiling particular classes of problems into logic programs.

1993
[3] Patrick Doherty and Dimiter Driankov. 1993.
Nonmonotonicity, fuzziness, and multi-values.
In R. Lowen and M. Roubens, editors, Fuzzy Logic: State of the Art. Series D: System Theory, Knowledge Engineering and Problem Solving.. In series: Volume 12 #12. Kluwer Academic Publishers. ISBN: 0792323246, 9780792323242.

1992
[2] Patrick Doherty and Witold Lukaszewicz. 1992.
Distinguishing between facts and default assumptions.
In W. van der Hoek, editor, Non-Monotonic Reasoning and Partial Semantics. Ellis Horwood Workshops.. Ellis Horwood Ltd.. ISBN: 0136251463, 9780136251460.

[1] Dimiter Driankov and Patrick Doherty. 1992.
A non-monotonic fuzzy logic.
In Lotfi A. Zadeh, Janusz Kacprzyk, editors, Fuzzy Logic for the Management of Uncertainty, pages 171–190. John Wiley & Sons. ISBN: 0-471-54799-9.


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