Probabilistic Networks and Expert Systems
Exact Computational Methods for Bayesian Networks
Cowell, R.G., Dawid, P., Lauritzen, S.L., Spiegelhalter, D.J.
1st ed. 1999. Corr. 2nd printing, 1999, XII, 324 p.
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ISBN 978-0-387-98767-5
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ISBN 978-0-387-71823-1
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Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.
Content Level » Research
Keywords » Bayesian Network - Graphical model - Junction tree - Machine learning - Probability propagation
Related subjects » Artificial Intelligence - Physical & Information Science - Probability Theory and Stochastic Processes - Statistical Theory and Methods
Table of contents
Introduction.- Logic, Uncertainty, and Probability.- Building and Using Probabilistic Networks.- Graph Theory.- Markov Properties on Graphs.- Discrete Networks.- Gaussian and Mixed Discrete-Gaussian Networks.- Discrete Multistage Decision Networks.- Learning About Probabilities.- Checking Models Against Data.- Structural Learning.
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