We investigate the behaviour of some locally interactive learning systems for a finite population of players. We assume that each player is matched with his neighbouring players to play a Coordination Game.
Players adopt boundedly rational rules of behaviour and update their strategy choices with inertia.
Learning and experimentation are entirely motivated by payoff considerations. We analyze the asymptotic properties of the aggregate system and we prove convergence to absorbing states, which we characterize. We report on the results of some simulations carried out on a Cellular Automaton hardware board that simulates a Torus of size 256 x 256 at a speed of 60 frames per second.