Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach - Softcover

Xiang, Yang

Softcover

ISBN 10: 0521153905 ISBN 13: 9780521153904

Publisher: Cambridge University Press, 2010

Synopsis

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 decade's research.

About this title

Book Description

To maintain today's ever-more-complex computer systems, there is a growing need for intelligent agents that can cooperate on complex tasks in an uncertain environment. In applications as diverse as equipment diagnosis, engineering design, sensor networks, area monitoring, and situation assessment, such agents must be able to use limited information and observatins to assess the state of their environment and take appropriate actions. This book identifies the technical challenges in building intelligent agents and provides a rigorous framework for meeting these challenges. It is the first book that addresses the subject of probabilistic inference by multiple agents using graphical knowledge representations.

Review

Review of the hardback: '... this is a valuable and welcome comprehensive guide to the state-of-the-art in applying belief networks.' Kybernetes

Review of the hardback: '... the well-balanced treatment of multiagent systems will make the book useful to both theoretical computer scientists and the more applied artificial intelligence community. Moreover, the interdisciplinary nature of the subject makes it relevant not only to computer scientists but also to people from operations research and microeconomics (social choice and game theory in particular). The book easily deserves to be on the shelf of any modern theoretical computer scientist.' SIGACT News

Edition details

• Publisher: Cambridge University Press
• Publication date: 2010
• Language: English
• ISBN 10: 0521153905
• ISBN 13: 9780521153904
• Binding: Paperback
• Edition number: 1
• Number of pages: 308