Probabilistic reasoning multiagent systems de xiang yang (36 resultados)

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Condición: New. Addresses the challenges of building intelligent agents to cooperate on complex tasks in uncertain environments. Num Pages: 308 pages, Illustrations. BIC Classification: PBT; UYA. Category: (P) Professional & Vocational. Dimension: 244 x 170 x 16. Weight in Grams: 490. . 2010. 1st Edition. paperback. . . . .…

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Condición: New. Addresses the challenges of building intelligent agents to cooperate on complex tasks in uncertain environments. Num Pages: 308 pages, Illustrations. BIC Classification: PBT; UYA. Category: (P) Professional & Vocational. Dimension: 244 x 170 x 16. Weight in Grams: 490. . 2010. 1st Edition. paperback. . . . . Books ship from the US and Ireland.…

Condición: Used. pp. 308 Index.

Taschenbuch. Condición: 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.…

Condición: Used. pp. 308 Illus.

Condición: Used. pp. 308.

Condición: New.

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Condición: 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. . . . . …

Condición: New. In English.

paperback. Condición: New. New .Ships From Multiple Locations. book.

Condición: 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. Condición: 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.…

Condición: New. Print on Demand pp. 308 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam.

Condición: New. Print on Demand pp. 308.

Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Condición: New. PRINT ON DEMAND pp. 308.

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