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Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach Hardback - 2002
by Xiang, Yang
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- Hardback
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Details
- Title Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach
- Author Xiang, Yang
- Binding Hardback
- Edition 1st
- Condition Used - Good
- Pages 308
- Volumes 1
- Language ENG
- Publisher Cambridge University Press
- Publication date 2002-08-26
- Illustrated Yes
- Features Bibliography, Illustrated, Index, Table of Contents
- Bookseller's Inventory # C160326ahmug174511
- ISBN 9780521813082 / 0521813085
- Weight 1.67 lbs (0.76 kg)
- Dimensions 9.98 x 7.08 x 0.93 in (25.35 x 17.98 x 2.36 cm)
- Size 7x1x9
- Category Computers - General Information
- Library of Congress subjects Intelligent agents (Computer software), Bayesian statistical decision theory - Data
- Library of Congress Catalogue Number 2001052874
- Dewey Decimal Code 006.3
- Quantity available 1
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Summary
This book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become an active field of research and practice in artificial intelligence, operations research and statistics in the last two decades. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. In this book, the author extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results from a decade's research. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.
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From the publisher
First line
An intelligent agent is a computational or natural system that senses its environment and takes actions intelligently according to its goals.
