In this paper, the genetic algorithm is used to investigate the evolution of cooperation based upon automata that play in an iterated prisoner’s dilemma tournament. Cooperation evolved from a state of randomness. Furthermore, it is shown that “niceness”, as defined by Robert Axelrod, is unstable in this model, and, contrary to previous speculation, selective pressure is needed to stabilize niceness. A multiprocessing approach also shows that cooperation can spread through migration among multiple evolving populations.
