Bayesian Networks and Decision Graphs / Edition 1

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Maths for engineers; Maths for scientists; Probabi

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Overview

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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Product Details

Table of Contents

Preface
I A Practical Guide to Normative Systems 1
1 Causal and Bayesian Networks 3
2 Building Models 35
3 Learning, Adaptation, and Tuning 79
4 Decision Graphs 109
II Algorithms for Normative Systems 157
5 Belief Updating in Bayesian Networks 159
6 Bayesian Network Analysis Tools 201
7 Algorithms for Influence Diagrams 225
List of Notation 253
Bibliography 255
Index 263
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