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Bayesian Belief Nets

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Belief nets (aka Bayesian Networks, probability nets, causal nets) are models for representing uncertainty in our knowledge.  Uncertainty arises in a variety of situations:

Belief Nets use probability theory to manage uncertainty by explicitly representing the conditional dependencies between the different knowledge components. This provides an intuitive graphical visualization of the knowledge including the interactions among the various sources of uncertainty.

General information about Belief Nets:

Overview textbooks:


Articles from the popular press

Technical Articles

Research Groups

Software for Belief Networks (inference, learning)
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