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Book Review: Bayesian Artificial Intelligence

Book Review: Bayesian Artificial Intelligence Artificial Intelligence and Law 11: 289–298, 2003. Book review Kevin B. Korb and Ann E. Nicholson, Bayesian Artificial Intelligence, Chapman & Hall/CRC, 2003, 392 pp. (ISBN 1-58488-387-1) 1. Introduction This is a review of Korb and Nicholson’s recent primer on Bayesian belief networks. Before giving my review, I would like to quote a passage from that book. On page 18, the authors write that The legal system is replete with misapplications of probability and with incorrect claims of the irrelevance of probabilistic reasoning as well. Although legal reasoning is not mentioned that much in the rest of the book, my hope is that this quote stirs up some interest, and serves well as a teaser for the rest of this review. I will return to this quote at the end. One of the motives to use probability theory in legal reasoning is that much legal reasoning is reasoning about evidence, and that much reasoning about evidence is reasoning with uncertain, incomplete or inconsistent information. One of the most prominent theories of reasoning with uncertain information is the theory of Bayesian belief networks. Hence it seems reasonable to investigate the applicability of Bayesian belief networks to the field of evidential http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence and Law Springer Journals

Book Review: Bayesian Artificial Intelligence

Artificial Intelligence and Law , Volume 11 (4) – Nov 7, 2004

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Publisher
Springer Journals
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Computer Science; Artificial Intelligence (incl. Robotics); International IT and Media Law, Intellectual Property Law; Philosophy of Law; Legal Aspects of Computing; Information Storage and Retrieval
ISSN
0924-8463
eISSN
1572-8382
DOI
10.1023/B:ARTI.0000045970.25670.25
Publisher site
See Article on Publisher Site

Abstract

Artificial Intelligence and Law 11: 289–298, 2003. Book review Kevin B. Korb and Ann E. Nicholson, Bayesian Artificial Intelligence, Chapman & Hall/CRC, 2003, 392 pp. (ISBN 1-58488-387-1) 1. Introduction This is a review of Korb and Nicholson’s recent primer on Bayesian belief networks. Before giving my review, I would like to quote a passage from that book. On page 18, the authors write that The legal system is replete with misapplications of probability and with incorrect claims of the irrelevance of probabilistic reasoning as well. Although legal reasoning is not mentioned that much in the rest of the book, my hope is that this quote stirs up some interest, and serves well as a teaser for the rest of this review. I will return to this quote at the end. One of the motives to use probability theory in legal reasoning is that much legal reasoning is reasoning about evidence, and that much reasoning about evidence is reasoning with uncertain, incomplete or inconsistent information. One of the most prominent theories of reasoning with uncertain information is the theory of Bayesian belief networks. Hence it seems reasonable to investigate the applicability of Bayesian belief networks to the field of evidential

Journal

Artificial Intelligence and LawSpringer Journals

Published: Nov 7, 2004

References