Expert systems and probabilistic network models
Author(s)
Bibliographic Information
Expert systems and probabilistic network models
（Monographs in computer science）
Springer, c1997
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Note
Includes bibliographical references (p. [581]-596) and index
Description and Table of Contents
Description
Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.
Table of Contents
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.
by "Nielsen BookData"