Computational Logic in Multi-Agent Systems

1. Front Matter

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2. Invited Papers

   1. Distributed Algorithms for Dynamic Survivability of Multiagent Systems

      • V. S. Subrahmanian, Sarit Kraus, Yingqian Zhang

      Pages 1-15

   2. Programming Groups of Rational Agents

      • Michael Fisher, Chiara Ghidini, Benjamin Hirsch

      Pages 16-33

3. Negotiation in Multi-agent Systems

   1. An Abductive Framework for Information Exchange in Multi-agent Systems

      • Marco Gavanelli, Evelina Lamma, Paola Mello, Paolo Torroni

      Pages 34-52

   2. Fault Tolerant and Fixed Scalable Structure of Middle-Agents

      • Pavel Tichý

      Pages 53-70

   3. Symbolic Negotiation with Linear Logic

      • Peep Küngas, Mihhail Matskin

      Pages 71-88

4. Planning in Multi-agent Systems

   1. Planning Experiments in the DALI Logic Programming Language

      • Stefania Costantini, Arianna Tocchio

      Pages 89-107

   2. A New HTN Planning Framework for Agents in Dynamic Environments

      • Hisashi Hayashi, Kenta Cho, Akihiko Ohsuga

      Pages 108-133

5. Knowledge Revision and Update in Multi-agent Systems

   1. Revising Knowledge in Multi-agent Systems Using Revision Programming with Preferences

      • Inna Pivkina, Enrico Pontelli, Tran Cao Son

      Pages 134-158

   2. A New Framework for Knowledge Revision of Abductive Agents Through Their Interaction

      • Andrea Bracciali, Paolo Torroni

      Pages 159-177

   3. Weighted Multi Dimensional Logic Programs

      • Pierangelo Dell’Acqua

      Pages 178-200

   4. (Dis)Belief Change Based on Messages Processing

      • Laurent Perrussel, Jean-Marc Thévenin

      Pages 201-217

6. Learning in BDI Multi-agent Systems

   1. Learning in BDI Multi-agent Systems

      • Alejandro Guerra-Hernández, Amal El Fallah-Seghrouchni, Henry Soldano

      Pages 218-233

   2. The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic Rules

      • Christopher Child, Kostas Stathis

      Pages 234-249

7. Back Matter

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Over recent years, the notion of agency has claimed a major role in de?ning the trends of modern research. In?uencing a broad spectrum of disciplines such as sociology, psychology, philosophy and many more, the agent paradigm virtually invaded every sub?eld of computer science, because of its promising applications for the Internet and in robotics. Multi-agent systems (MAS) are communities of problem-solving entities that can perceive and act upon their environments to achieve their individual goals as well as joint goals. The work on such systems integrates many technologies and concepts in arti?cial intelligence and other areas of computing. There is a full spectrum of MAS applications that have been and are being developed: from search engines to educational aids to electronic commerce and trade. Although commonly implemented by means of imperative languages, mainly for reasons of e?ciency, the agent concept has recently increased its in?uence in the research and development of computational logic-based systems. Computational logic, by virtue of its nature both in substance and method, providesawell-de?ned,general,andrigorousframeworkforsystematicallystu- ing computation, be it syntax, semantics, and procedures, or implementations, environments, tools, and standards. Computational logic approaches problems, and provides solutions, at a su?cient level of abstraction so that they generalize from problem domain to problem domain, a?orded by the nature of its very foundation in logic, both in substance and method, which constitutes one of its major assets.

• AI logics
• BDI agents
• MAS
• agent communication
• algorithms
• computational logic
• formal methods
• formal reasoning
• knowledge processing
• learning
• logic
• logic programming
• mathematical logic
• multi-agent system
• multi-agent systems

• Clausthal University of Technology, Clausthal-Zellerfeld, Germany

  Jürgen Dix

• Departamento de Informática, Universidade Nova de Lisboa, Caparica, Portugal

  João Leite

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