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Synopsis
Addresses the challenges of building intelligent agents to cooperate on complex tasks in uncertain environments.
Booknews
Investigating the use of Bayesian networks or belief networks for building intelligent decision support systems, Xiang (computing and information science, U. of Guelph, Canada) extends the application of these graphical dependence models from the centralized and single- agent paradigm to representation formalisms under the distributed and multiagent paradigm. After identifying the technical challenges to such an application, he presents his research on the matter. The foci of the work is the structuring of multiple agents' knowledge as a set of probabilistic graphical models, the compilation of the models into graphical structures for message passing, and the use of message passing to accomplish tasks in model verification and compilation and distributed interference. Annotation c. Book News, Inc., Portland, OR