Isbn: 9780521813082 - probabilistic reasoning in multiagent systems: a graphical models approach (26 Ergebnisse)

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Zustand: New. Addresses the challenges of building intelligent agents to cooperate on complex tasks in uncertain environments. Num Pages: 308 pages, 185 b/w illus. 22 tables. BIC Classification: PBT; UYA. Category: (P) Professional & Vocational. Dimension: 247 x 174 x 19. Weight in Grams: 764. . 2002. Illustrated. hardcover. . . . . …

Zustand: New. Addresses the challenges of building intelligent agents to cooperate on complex tasks in uncertain environments. Num Pages: 308 pages, 185 b/w illus. 22 tables. BIC Classification: PBT; UYA. Category: (P) Professional & Vocational. Dimension: 247 x 174 x 19. Weight in Grams: 764. . 2002. Illustrated. hardcover. . . . . Books ship from the US and Ireland. …

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This 2002 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 increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang 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. 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.…

Hardcover. Zustand: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 s.…

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Buch. Zustand: Neu. Probabilistic Reasoning in Multiagent Systems | A Graphical Models Approach | Yang Xiang | Buch | Gebunden | Englisch | 2010 | Cambridge University Press | EAN 9780521813082 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…