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Bayesian networks and decision graphs. 2nd ed. (English) Zbl 1277.62007
Information Science and Statistics. New York, NY: Springer (ISBN 978-0-387-68281-5/hbk; 978-0-387-68282-2/ebook). xvi, 447 p. (2007).
Publisher’s description: This is a new edition of the book [Zbl 0973.62005] by Finn V. Jensen. The new edition is structured into two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems.

MSC:
62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62C10 Bayesian problems; characterization of Bayes procedures
62F15 Bayesian inference
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
94C15 Applications of graph theory to circuits and networks
90C40 Markov and semi-Markov decision processes
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