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Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach by Ya

Description: Probabilistic Reasoning in Multiagent Systems by Yang Xiang This book identifies the technical challenges in building intelligent agents that can cooperate on complex tasks in an uncertain environment and provides a rigorous framework for meeting these challenges. It addresses the subject of probabilistic inference by multiple agents using graphical knowledge representations. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description 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 decades 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. Table of Contents Preface; 1. Introduction; 2. Bayesian networks; 3. Belief updating and cluster graphs; 4. Junction tree representation; 5. Belief updating with junction trees; 6. Multiply sectioned Bayesian networks; 7. Linked junction forests; 8. Distributed multi-agent inference; 9. Model construction and verification; 10. Looking into the future; Bibliography; Index. Review ... this is a valuable and welcome comprehensive guide to the state-of-the-art in applying belief networks. Kybernetes Promotional Addresses the challenges of building intelligent agents to cooperate on complex tasks in uncertain environments. Long Description Probalistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become an active field of research and practice in artifical 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 paradim 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 gleaned from a decades research. Review Quote … this is a valuable and welcome comprehensive guide to the state-of-the-art in applying belief networks. Kybernetes Promotional "Headline" Addresses the challenges of building intelligent agents to cooperate on complex tasks in uncertain environments. Description for Bookstore This 2002 book identifies the technical challenges in building intelligent agents that can cooperate on complex tasks in an uncertain environment and provides a rigorous framework for meeting these challenges. It is a comprehensive book that addresses the subject of probabilistic inference by multiple agents using graphical knowledge representations. Description for Library This 2002 book identifies the technical challenges in building intelligent agents that can cooperate on complex tasks in an uncertain environment and provides a rigorous framework for meeting these challenges. It is a comprehensive book that addresses the subject of probabilistic inference by multiple agents using graphical knowledge representations. Details ISBN0521813085 Author Yang Xiang Short Title PROBABILISTIC REASONING IN MUL Publisher Cambridge University Press Language English ISBN-10 0521813085 ISBN-13 9780521813082 Media Book Format Hardcover Illustrations Yes Year 2002 Imprint Cambridge University Press Subtitle A Graphical Models Approach Place of Publication Cambridge Country of Publication United Kingdom Birth 1954 Affiliation University of Guelph, Ontario DOI 10.1604/9780521813082 UK Release Date 2002-08-26 AU Release Date 2002-08-26 NZ Release Date 2002-08-26 Pages 308 Publication Date 2002-08-26 Alternative 9780511546938 DEWEY 519.2 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:91370598;

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Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach by Ya

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ISBN-13: 9780521813082

Book Title: Probabilistic Reasoning in Multiagent Systems

Number of Pages: 308 Pages

Language: English

Publication Name: Probabilistic Reasoning in Multiagent Systems: a Graphical Models Approach

Publisher: Cambridge University Press

Publication Year: 2002

Subject: Computer Science, Mathematics

Item Height: 254 mm

Item Weight: 764 g

Type: Textbook

Author: Yang Xiang

Item Width: 178 mm

Format: Hardcover

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