Multiagent Systems

ISBN-13: 9780521899437 / Angielski / Twarda / 2008 / 504 str.

Yoav Shoham

Opis

This exciting and pioneering new overview of multiagent systems, which are online systems composed of multiple interacting intelligent agents, i.e., online trading, offers a newly seen computer science perspective on multiagent systems, while integrating ideas from operations research, game theory, economics, logic, and even philosophy and linguistics. 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. Written by two of the leading researchers of this engaging field, this book will surely serve as THE reference for researchers in the fastest-growing area of computer science, and be used as a text for advanced undergraduate or graduate courses.

Recenzje

'... 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

Spis treści

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.

O autorze

Leyton-Brown, KevinKevin 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).