Contributions To Game Theoretic Aspects Of Multi Agent Systems


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Contributions to Game-theoretic Aspects of Multi-agent Systems


Contributions to Game-theoretic Aspects of Multi-agent Systems

Author: Ryan W. Porter

language: en

Publisher:

Release Date: 2004


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Argumentation in Multi-Agent Systems


Argumentation in Multi-Agent Systems

Author: Peter McBurney

language: en

Publisher: Springer

Release Date: 2012-02-21


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This book constitutes the thoroughly reviewed post-proceedings of the 7th International Workshop on Argumentation in Multi-Agent Systems, ArgMas 2010, held in Toronto, Canada in May 2010 as a satellite workshop of AAMAS 2010. The 14 revised full papers taken from ArgMAS 2010 were carefully reviewed and improved during two rounds of revision. Also included are 4 invited papers based on presentations on argumentation at the AAMAS 2010 main conference. All together the 18 papers included in the book give a representative overview on current research on argumentation in multi-agent systems. The papers are organized in topical sections on practical reasoning and argument about action, applications, and theoretical aspects.

Multiagent Systems


Multiagent Systems

Author: Yoav Shoham

language: en

Publisher: Cambridge University Press

Release Date: 2008-12-15


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Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming.