Updated and expanded, Bayesian Artificial Intelligence, Second
Edition provides a practical and accessible introduction to the
main concepts, foundation, and applications of Bayesian networks.
It focuses on both the causal discovery of networks and Bayesian
inference procedures. Adopting a causal interpretation of Bayesian
networks, the authors discuss the use of Bayesian networks for
causal modeling. They also draw on their own applied research to
illustrate various applications of the technology. New to the
Second Edition New chapter on Bayesian network classifiers New
section on object-oriented Bayesian networks New section that
addresses foundational problems with causal discovery and Markov
blanket discovery New section that covers methods of evaluating
causal discovery programs Discussions of many common modeling
errors New applications and case studies More coverage on the uses
of causal interventions to understand and reason with causal
Bayesian networks Illustrated with real case studies, the second
edition of this bestseller continues to cover the groundwork of
Bayesian networks. It presents the elements of Bayesian network
technology, automated causal discovery, and learning probabilities
from data and shows how to employ these technologies to develop
probabilistic expert systems. Web Resource The book's website at
www.csse.monash.edu.au/bai/book/book.html offers a variety of
supplemental materials, including example Bayesian networks and
data sets. Instructors can email the authors for sample solutions
to many of the problems in the text.
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