Bayesian Networks
A Bayesian network (BN) is a graphical representation based on probability theory. It is a directed acyclic graph with nodes, arcs, tables, and their associated probability values. These probabilities may be used to reason or make inferences within the system. Further, BNs have distinct advantages compared to other methods, such as neural networks, decision trees, and rule bases, when it comes to modeling a diagnostic system. One of the many reasons why Bayesian networks are preferred over decision trees is that in BN, it is possible to traverse both ways. Recent developments in this area include new and more efficient inference methods, as well as universal tools for the design of BN-based applications. An extended list of software for BNs is at http://bayes.stat.washington.edu/almond/ belief.html.
http://www.niedermayer.ca/ papers/bayesian/bayes.html