Learning in Games.

In a Nash equilibrium, each player selects a strategy that is optimal with respect to the strategies of other players. This definition does not mention the process by which players reach a Nash equilibrium. The topic of learning in games seeks to address this issue in that it explores how simplistic learning/adaptation rules can lead to Nash equilibrium. This article presents a selective sampling of learning rules and their long-run convergence properties, i.e., conditions under which player strategies converge or not to Nash equilibrium.