This paper studies overlapping generations economies in which agents use genetic algorithms to learn correct decision rules. The results of computer simulations show that a genetic algorithm converges to the unique monetary steady state in case of a constant money supply policy and to the low-inflation stationary equilibrium in case of a constant real deficit financed through seignorage. Features of the genetic algorithm adaptation are compared to the performance of other learning algorithms and to the behavior observed in experiments with human subjects in the same OLG environments.