Agents and Multi-Agent Systems : Formalisms, Methodologies and Applications : Based on the Ai'97 Workshop on Commonsense Reasoning, Intelligent Agents, and Distributed Artificial

Wobcke, Wayne (EDT); Pagnucco, Maurice; Zhang, Chengqi (EDT)

ISBN 10: 3540647694 / ISBN 13: 9783540647690

Editore: Springer, 1998

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Dati bibliografici

• Titolo: Agents and Multi-Agent Systems : Formalisms, Methodologies and Applications : Based on the Ai'97 Workshop on Commonsense Reasoning, Intelligent Agents, and Distributed Artificial
• Editore: Springer
• Data di pubblicazione: 1998
• Lingua: Inglese
• ISBN 10: 3540647694
• ISBN 13: 9783540647690
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

This book constitutes the thoroughly refereed post-workshop proceedings of three workshops held in conjunction with the 10th Australian Joint Conference on Artificial Intelligence in Perth, Australia, in December 1997.
The 17 revised full papers presented were carefully reviewed for inclusion in the book. The book is divided into sections on formal methods of agency, reasoning agents, communication and coordination, social interaction, and practical issues for distributed artificial intelligence systems.

Contenuti

Specifying communicative multi-agent systems.- Making it up as they go along: A theory of reactive cooperation.- Agency and the logic of ability.- On the relation between interpreted systems and Kripke models.- Disjunctive logic programming and possible model semantics.- A non-monotonic ATMS based on annotated logic programs with strong negation.- Switching between reasoning and search.- The social dimension of interactions in multiagent systems.- Generating states of joint commitment between autonomous agents.- Social co-ordination among autonomous problem-solving agents.- An algorithm for plan verification in multiple agent systems.- A framework for coordination and learning among teams of agents.- An iterated hawk-and-dove game.- A game-theoretic solution of conflicts among competitive agents.- Transformation between the EMYCIN model and the Bayesian network.- Using multi-agent approach for the design of an intelligent learning environment.- A case-based strategy for solution synthesis among cooperative expert systems.