Improving the Discovery Component of Classifier Systems by the application of Estimation of Distribution Algorithms

Since Holland and Reitman [2] published their CS-1 a great amount of studies concerning classifiers systems (CSs) have appeared. The needs of studying crucial matters in the functioning of CS determined that researchers paid little attention to the evolutionary component of these systems. Nevertheless in the last years GA's have experienced a considerable development that makes necessary to revise an update current applications of EA's to CSs. The goal of our current research is to incorporate to the CS's machinery new Evolutionary Techniques that make of them more powerful machine learning tools. In this paper we introduce an Estimation Distribution Algorithm to perform as the discovery component of the classifier system XCS.