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.
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(253mm x 177mm x 27mm)
Cambridge University Press
Publisher: Cambridge University Press
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Author Biography - Yoav Shoham
Yoav Shoham is Professor of Computer Science at Stanford University, where he has been since receiving his PhD in computer science from Yale University in 1987. Shoham is a Fellow of the Association for Advancement of Artificial Intelligence (AAAI) and charter member of the International Game Theory Society. Aside from authoring four books and numerous other works, he is director of TARK (Theoretical Aspects of Rationality and Knowledge), a non-profit organization. Kevin Leyton-Brown is an Assistant Professor of Computer Science at the University of British Columbia. His affiliations include the Laboratory for Computational Intelligence (LCI) and the Bioinformatics, and Empirical and Theoretical Algorithmics Laboratory (BETA-Lab) and membership on the editorial board of the Journal of AI Research (JAIR).