Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the ways to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover rules that govern emergent cooperative behavior. A self-organizing genetic algorithm was applied to automating the discovery of rules for multi-agents playing soccer. A model consisting of movable agents in a cellular space is introduced. Simulation results indicate that, given the complexity of the problem an evolutionary approach to finding the appropriate rules seems to be promising. The implications of the results are discussed. (C) Elsevier Science Inc., 1997.