A Genetic Algorithm to Study a P3 Non-trivial Collective Task

Abstract

Here we report new results of a genetic algorithm (GA) used to evolve one dimensional Cellular Automata (CA) to perform a P3 non-trivial collective behavior task. For this task the goal is to find a CA rule that reaches one final configuration in which the concentration of active cells oscillates among three different values. Though the majority of the best evolved rules belong to the II Wolfram’s class, the GA also finds rules of the III and IV classes. The different computational mechanisms used by each rule to synchronize the entire lattice are analyzed by means of the spatio-temporal patterns generated.