Coevolving Cellular Automata: Be Aware of the Red Queen!

Abstract

This paper studies the use of coevolution to search for a cellular automaton (CA) solving the well-known density classification task. The Coevolutionary Genetic Algorithm (CGA) coevolves two non-interbreeding populations which interact as predator and prey. The main purpose of this paper is to illustrate some of the intricacies involved in the use of coevolution to solve a given task. Concepts from standard GA theory can be used to understand these problems. A simple modification is proposed to significantly increase the performance. 1 INTRODUCTION In nature, predator-prey interactions provide a driving force towards complexity. This because there is a strong evolutionary pressure for prey to defend themselves better (e.g. by running quicker, growing bigger shields, better camouflage ...) in response to which future generations of predators develop better attacking strategies (e.g. stronger claws, better eye-sight ...). Such arms races are characterized by an inverse fitness interactio..