Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks / Edition 1

by Robert G. Cowell, Philip Dawid, Steffen L. Lauritzen, David J. Spiegelhalter

Overview

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.

Product Details

ISBN-13:	9780387718231
Publisher:	Springer New York
Publication date:	07/16/2007
Series:	Information Science and Statistics
Edition description:	1999
Pages:	324
Product dimensions:	6.10(w) x 9.20(h) x 0.70(d)

Table of Contents

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.

Editorial Reviews

From the reviews:

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

"This important book fills a void in the graphical Markov models literature. The authors have summarized their extensive and influential work in this area and provided a valuable resource both for educators and for practitioners."

From the Publisher