Structure Learning of Bayesian Networks by Genetic Algorithms

This paper begins with an introduction to the Bayesian Network paradigm, followed by a brief enumeration of some of the current approaches in the induction of structure learning in Bayesian Networks. We will present our approach, in one artificial domain with two types of Genetic Algorithms (Simple, Elitist) using them as optimizers, in combination with the experimental results we have obtained. The paper closes with the conclusions and potential further research in this field.