Multiagent systems: algorithmic, game-theoretic, and logical foundations

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.

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.

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