Probabilistic Reasoning in Multiagent Systems

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 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.

subjects: Computer Technology,  Nonfiction,  Bayesian statistical decision theory,  Intelligent agents (Computer software),  Distributed artificial intelligence,  Data processing,  Artificial intelligence,  Intelligence artificielle répartie,  Théorie de la décision bayésienne,  Agents intelligents (Logiciels),  COMPUTERS,  Enterprise Applications,  Business Intelligence Tools,  Intelligence (AI) & Semantics,  Agentia,  Kunstmatige intelligentie,  Gedistribueerde gegevensverwerking,  Methode van Bayes,  Decision support systems,  Grafische methoden