The structure of evolutionary exploration: On crossover, buildings blocks and Estimation-Of-Distribution Algorithms

Abstract

The notion of building blocks can be related to the structure of the offspring probability distribution: loci of which variability is strongly correlated constitute a building block. We call this correlated exploration. With this background we analyze the structure of the offspring probability distribution, or exploration distribution, for a GA with mutation only, a crossover GA, and an Estimation-Of-Distribution Algorithm (EDA). The results allow a precise characterization of the structure of the crossover exploration distribution. Essentially, the crossover operator destroys mutual information between loci by transforming it into entropy; it does the inverse of correlated exploration. In contrast, the objective of EDAs is to model the mutual information between loci in the fitness distribution and thereby they induce correlated exploration.