Bayesian Artificial Intelligence (Chapman & Hall/CRC Computer Science & Data Analysis)

Korb, Kevin B.; Nicholson, Ann E.

ISBN 10: 1584883871 / ISBN 13: 9781584883876

Published by Chapman and Hall/CRC, 2003

About this Item

~ NEW inside and Out! Clean & Crisp Pages w/No markings. (Email for more info./pics).

Seller Inventory # 221127072

Bibliographic Details

• Title: Bayesian Artificial Intelligence (Chapman & Hall/CRC Computer Science & Data Analysis)
• Publisher: Chapman and Hall/CRC
• Publication Date: 2003
• Language: English
• ISBN 10: 1584883871
• ISBN 13: 9781584883876
• Binding: hardcover
• Condition: New
• Weight: 25 ounces
• Seller catalogs:
  • Education/Textbooks

About this title

Synopsis

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.

About the Author

Kevin B. Korb is a Reader in the Clayton School of Information Technology at Monash University in Australia. He earned his Ph.D. from Indiana University. His research encompasses causal discovery, probabilistic causality, evaluation theory, informal logic and argumentation, artificial evolution, and philosophy of artificial intelligence.

Ann E. Nicholson an Associate Professor in the Clayton School of Information Technology at Monash University in Australia. She earned her Ph.D. from the University of Oxford. Her research interests include artificial intelligence, probabilistic reasoning, Bayesian networks, knowledge engineering, plan recognition, user modeling, evolutionary ethics, and data mining