Welcome: Probability Theory and Bayesian Belief Bayesian Networks


Note: This web page is no longer being maintained. Additional material is being maintained here, here and here. Much of this material is covered in the book Fenton, N.E. and M. Neil, Risk Assessment with Bayesian Networks CRC Press, 2012


A Bayesian Network (also called Bayesian belief network, belief network, Bayesian net, BBN, BN or graphical probability model) is a model for reasoning about uncertainty. Founded on the centuries-old Bayesian probability theory (invented by Thomas Bayes in 1763), the subject has been given a lease of life in recent years due to advances in algorithms and theory. These advances mean that it is now possible to build and run realistic Bayesian nets for a wide range of applications. This web contains detailed information on the following

Probability Theory
Bayesian belief networks: an overview
Bayesian belief networks: a detailed account
Biases and fallacies in reasoning about probability
Bayesian nets and Bayesian Probability Resources

For readers who are seeking an excellent tool for building Bayesian Network applications, go to the Agena website

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