Co-evolution for cooperative behavior acquisition in a multiple mobile robot environment

Abstract

Co-evolution has been receiving increased attention as a method for multi agent simultaneous learning. This paper discusses how multiple robots can emerge cooperative behaviors through co-evolutionary processes. As an example task, a simplified soccer game with three learning robots is selected and a genetic programming method is applied to individual population corresponding to each robot so as to obtain cooperative and competitive behaviors. The complexity of the problem can be explained twofold: co-evolution for cooperative behaviors needs exact synchronization of mutual evolutions, and three robot co-evolution requires well-complicated environment setups that may gradually change from, simpler to more complicated situations. Simulation results are shown, and a discussion is given.