An Introduction to Belief Networks

7/2/99


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Table of Contents

An Introduction to Belief Networks

Belief Networks

Probabilistic Knowledge

What can they compute

Degrees of Belief

Random Variables

Probability Distribution

Joint Probability Distribution

An Example of a JPD (flattened)

The Axioms of Probability

Conditional Probabilities

Bayes’ Rule

Independence

A Belief Network

d-Separation [Pearl]

Examples of d-separation

A BN is a complete model

Other ways to compute CPTs

Noisy-OR

Noisy-OR (Example)

Complexity

Expressiveness

References

Author: Dimitrios Liarokapis

Email: dimitris@cs.umb.edu

Home Page: www.cs.umb.edu/~dimitris