
Bayesian Artificial Intelligence
Chapman & Hall/CRC (Publisher)
1st Edition
Published on 25. September 2003
Book
Hardback
392 pages
978-1-58488-387-6 (ISBN)
Article exhausted; check for reprint
Description
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.
More details
Series
Language
English
Place of publication
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Illustrations
106 s/w Abbildungen
106 Illustrations, black and white
Dimensions
Height: 235 mm
Width: 159 mm
Weight
703 gr
ISBN-13
978-1-58488-387-6 (9781584883876)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Kevin B. Korb | Ann E. Nicholson
Bayesian Artificial Intelligence
Book
12/2010
2nd Edition
CRC Press
€207.30
Shipment within 15-20 days
Persons
Author
Monash University, Clayton, Victoria, Australia
Monash University, Clayton, Victoria, Australia
Content
Bayesian Reasoning. Introduction to Bayesian Networks. Inference in Bayesian Networks. Bayesian Network Applications. Bayesian Planning and Decision-Making. Bayesian Network Applications II. Learning Bayesian Networks I. Learning Bayesian Networks II. Causality vs. Probability. Knowledge Engineering with Bayesian Networks I. Knowledge Engineering with Bayesian Networks II. Application Software.