This is a brand new edition of an essential work on Bayesian
networks and decision graphs. It is an introduction to
probabilistic graphical models including Bayesian networks and
influence diagrams. The reader is guided through the two types of
frameworks with examples and exercises, which also give instruction
on how to build these models. Structured in two parts, the first
section focuses on probabilistic graphical models, while the second
part deals with decision graphs, and in addition to the frameworks
described in the previous edition, it also introduces Markov
decision process and partially ordered decision problems.
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