Multiagent Systems Algorithmic, Game-Theoretic, and Logical Foundations A thorough introduction to a burgeoning interdisciplinary field, with an emphasis on foundational material. Yoav Shoham (Author), Kevin Leyton-Brown (Author) 9780521899437, Cambridge University Press Hardback, published 15 December 2008 504 pages, 14 tables25.7 x 18.5 x 3.6 cm, 1.03 kg '… 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 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. 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. Subject Areas: Artificial intelligence [UYQ], Game theory [PBUD], Mathematical logic [PBCD]
