By Gerhard Weiss
This is the 1st complete creation to multiagent platforms and modern allotted synthetic intelligence that's compatible as a textbook. The e-book offers precise assurance of simple subject matters in addition to numerous heavily similar ones.
Unlike conventional textbooks, the e-book brings jointly many major specialists, making certain a extensive and various base of data and services. It emphasizes features of either thought and alertness, and offers many illustrations and examples. additionally incorporated are thought-provoking workouts of various levels of hassle and a twenty-page word list of phrases present in the examine of brokers, multiagent structures, and disbursed synthetic intelligence.
The publication can be utilized for educating in addition to self-study, and is designed to satisfy the desires of either researchers and practitioners. In view of the interdisciplinary nature of the sector, it will likely be an invaluable reference not just for computing device scientists and engineers, yet for social scientists and administration and association 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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Additional info for Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Example text
Proceedings of the First European Workshop on Modelling Autonomous Agents in a Multi-Agent World MAAMAW'89 . North-Holland, 1990. 14. Y. -P. Muller, editors. Decentralized Arti cial Intelligence. Proceedings of the Second European Workshop on Modelling Autonomous Agents in a Multi-Agent World MAAMAW'90 . Elsevier Science, 1991. 15. H. Durfee. The distributed arti cial intelligence melting pot. IEEE Transactions on Systems, Man, and Cybernetics, SMC-21 6 :1301 1306, 1991. 22 Prologue 16. H. Durfee, editor.
Respond to more diverse orders than individual agents can|but do not su er from diseconomies of scale. Automated negotiation can save labor time of human negotiators, but in addition, other savings are possible because computational agents can be more e ective at nding bene cial short-term contracts than humans are in strategically and combinatorially complex settings. This chapter discusses methods for making socially desirable decisions among rational agents that only care of their own good, and may act insincerely to promote it.
Distributed problem solving focuses on techniques for exploiting the distributed computational power and expertise in a MAS to accomplish large complex tasks. Of particular interest are strategies for moving tasks or results among agents to realize the bene ts of cooperative problem solving. One main thread of work is the development of taskpassing techniques to decide where to allocate subtasks to exploit the available capabilities of agents when large tasks initially arrive at a few agents. A second main thread of work is the study of result-sharing strategies to decide how agents that might be working on pieces of larger task can discover the relationships among their activities and coordinate them.