We present a simple model of spatial evolution that avoids several problems that arise with more complex networks of players. We consider a world where pairs of players are matched forever. These players learn from the whole population but they are more likely to learn to strategies used by...

The paper applies the idea of evolution to a spatial model. We assume that the prisoners' dilemma is played only within a neighborhood and that evolutionary pressure works also only on a local level. Discriminatory behavior of players is introduced representing strategies as small automata,...