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Multiagent Systems
Algorithmic, Game-Theoretic, and Logical Foundations

  • Date Published: December 2008
  • availability: Available
  • format: Hardback
  • isbn: 9780521899437

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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.

    • First rigorous introduction covering multiagent systems
    • Covers broad area including computer science, game theory, and logic
    • Does not require knowledge beyond typical undergraduate study and offers background material for probability theory, classical logic, and mathematical programming
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    Reviews & endorsements

    '… an excellent volume … It is the first book I have read that brings together the relevant mathematical results from such a wide variety of underlying disciplines. The writing is very clear, and the production standard is excellent … an invaluable reference manual for graduate students and researchers working on these topics … The price is appropriate for a volume of this type, especially as the book serves both to educate the reader and to serve as a reference manual.' Journal of the Operational Research Society

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    Product details

    • Date Published: December 2008
    • format: Hardback
    • isbn: 9780521899437
    • length: 504 pages
    • dimensions: 257 x 185 x 36 mm
    • weight: 1.07kg
    • contains: 14 tables
    • availability: Available
  • Table of Contents

    1. Distributed constraint satisfaction
    2. Distributed optimization
    3. Introduction to non-cooperative game theory
    4. Computing solution concepts of normal-form games
    5. Games with sequential actions
    6. Richer representations
    7. Learning and teaching
    8. Communication
    9. Aggregating preferences
    10. Protocols for strategic agents
    11. Protocols for multiagent resource allocation
    12. Teams of selfish agents
    13. Logics of knowledge and belief
    14. Beyond belief.

  • Instructors have used or reviewed this title for the following courses

    • Game-Theoretic Artificial Intelligence
    • Multi-Agent Systems
    • machine learning
  • Authors

    Yoav Shoham, Stanford University, California
    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, University of British Columbia, Vancouver
    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).

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