Sexy Evolutionary Computation

Abstract

The impact of Natural Selection overshadowed Darwin's Sexual Selection theory. However, over the past few decades it begun to draw the attention of researchers from several di erent elds and the amount of supporting evidence of its role in evolution rapidly increased. Today, although the dynamics aren't fully understood, the importance of sexual selection in evolution is undebatable. The enthusiasm around this eld was not followed by evolutionary computation. On the one hand, canonical evolutionary computation systems were already well-established when sexual selection re-surfaced. On the other, so far, attempts to incorporate sexual selection approaches in evolutionary computation, particularly when applied to optimization problems, have encountered several di culties and no generic tools and approaches applicable to a wide variety of problems exist. This dissertation constitutes a step towards changing this situation. Based on an embracing survey of the state of the art and following a natureinspired approach, a popular evolutionary computation framework is expanded through the incorporation of Mate Choice mechanisms { enabling the application of sexual selection models to a wide variety of problems with little e ort. The approach is tested on symbolic regression benchmark problems. The analysis of such problems indicates that sexual selection is able to outperform conventional approaches in complex problem instances. Additional testing and analysis focused on understanding how sexual selection contributes to the evolution. The experimental results show that the evolved mate choice functions are able to select mating partners in meaningful ways, contributing to the evolutionary success of the descendants.