Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence that is suitable as a textbook. The book provides detailed coverage of basic topics as well as several closely related ones.
Unlike traditional textbooks, the book brings together many leading experts, guaranteeing a broad and diverse base of knowledge and expertise. It emphasizes aspects of both theory and application, and provides many illustrations and examples. Also included are thought-provoking exercises of varying degrees of difficulty and a twenty-page glossary of terms found in the study of agents, multiagent systems, and distributed artificial intelligence.
The book can be used for teaching as well as self-study, and is designed to meet the needs of both researchers and practitioners. In view of the interdisciplinary nature of the field, it will be a useful reference not only for computer scientists and engineers, but for social scientists and management and organization scientists as well.
Contributors: Gul A. Agha, Kathleen M. Carley, Jose Cuena, Edmund H. Durfee, Clarence Ellis, Les Gasser, Michael P. Georgeff, Michael N. Huhns, Toru Ishida, Nadeem Jamali, Sascha Ossowski, H. Van Dyke Parunak, Anand S. Rao, Tuomas W. Sandholm, Sandip Sen, Munindar P. Singh, Larry M. Stephens, Gerard Tel, Jacques Wainer, Gerhard Weiss, Michael J. Wooldridge, Makoto Yokoo.
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Multiagent Systems and Societies of Agents
Distributed Problem Solving and Planning
Search Algorithms for Agents
Distributed Rational Decision Making
Learning in Multiagent Systems
Industrial and Practical Applications of DAI
Distributed Models for Decision Support
Concurrent Programming for DAI
Distributed Control Algorithms for AI
Constraint Satisfaction Problem CSP
Computational Organization Theory