Expert Systems and Probabilistic Network Models - Rilegato

Castillo, Enrique; Gutierrez, Jose Manuel; Hadi, Ali S.

Rilegato

ISBN 10: 0387948589 ISBN 13: 9780387948584

Casa editrice: Springer-Verlag New York Inc, 1996

Riassunto

Expert systems and uncertainty in artificial intelligence have seen a great surge of research activity during the last decade. This book provides a clear and up-to-date account of the research progress in these areas.
The authors begin with a survey of rule-based expert systems, which are mainly applicable to deterministic situations. Since most practical applications involve some degree of uncertainty, the authors then introduce probabilistic expert systems to deal with this element of uncertainty. They build on this foundation by showing how coherent expert systems are constructed and how probabilistic models such as Bayesian and Markov networks are developed. Subsequent chapters discuss how knowledge is updated by using both exact and approximate propagation methods. Other subjects such as symbolic propagation, sensitivity analysis, and learning are also presented. The book concludes with a chapter that applies the methods presented in the book to some case studies of real-life applications.
The concepts, ideas, and algorithms are illustrated by more than 150 examples and more than 250 graphs with the aid of computer programs developed by the authors. These programs can be obtained from a World Wide Web site (see the address in the preface). The book also includes end-of-chapter exercises and an extensive bibliography.
This book is intended for advanced undergraduate and graduate students, and for research workers and professionals from a variety of fields, including computer science, applied mathematics, statistics, engineering, medicine, business, economics, and social sciences. No previous knowledge of expert systems is assumed. Readers are assumed to have some background in probability and statistics.

Su questo libro

Contenuti

Contents: Rule-based expert systems.- Probabilistic expert systems.- Some concepts of graphs.- Building probabalistic models.- Graphically specified models.- Extending graphically specified models.- Exact propagation in probabilistic network models.- Approximate propagation methods.- Symbolic propagation of evidence.- Learning Bayesian models.- Case studies.

Product Description

Book by Castillo Enrique Gutierrez Jose M Hadi Ali S

Dettagli dell'edizione

• Editore: Springer-Verlag New York Inc
• Data di pubblicazione: 1996
• Lingua: Inglese
• ISBN 10: 0387948589
• ISBN 13: 9780387948584
• Rilegatura: Copertina rigida
• Numero di pagine: 605
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania