Introduction to Bayesian Networks

Bayesian networks are probabilistic causal models. The graph represents the structure of a domain knowledge, and probabilities represent the uncertain part of this domain. This chapter explains this idea with a very simple example in industrial safety. The first use of Bayesian networks is that of a “conditional probability calculator". Given a model, assumed to be constructed by an expert, the use of a Bayesian network amounts to calculating the probability of a nonobserved variable conditionally to the observed variables. A second domain of research for Bayesian networks is the automatic construction of models. This is a fascinating subject. Indeed, if we think about it, the notion of conditional probability…