The Bayesian Network is an easy-to-understand graphical notation representing the conditional inter-dependence of variables within a system. This simple graphical formalism can leverage conditional probability distributions to describe relationships between variables in a system. How can Bayesian networks compute the probabilities of specific events given other facts? Humans also use this kind of reasoning to render decisions in uncertain environments.
The term Bayesian network was coined by Judea Pearl in 1985 to emphasize:
In the late 1980s Pearl's Probabilistic Reasoning in Intelligent Systemsand Neapolitan's Probabilistic Reasoning in Expert Systems summarized their properties and established them as a field of study.