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Bayesian networks and decision graphs. (English) Zbl 0973.62005

Statistics for Engineering and Information Science. New York, NY: Springer. xv, 268 p. (2001).
This book is an introduction to Bayesian networks and decision graphs. It falls into two parts. In Part I, the emphasis is on gaining practical experience with the use of Bayesian networks as well as decision trees and influence diagrams. Through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics.
Part II is devoted to presenting basic algorithms for normative systems. The algorithms are exploited to introduce new types of features for decision support systems and bodyless agents. The exposition is also self-contained, but it is required that the reader is familiar with working with texts in the mathematical language.
The book addresses readers in both academia and industry who want to learn enough theory and technology to be able to build probabilistic expert systems.

MSC:

62C10 Bayesian problems; characterization of Bayes procedures
62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
94C15 Applications of graph theory to circuits and networks
05C90 Applications of graph theory
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