A general approach to rational learning in games

This paper provides a general framework for analysing rational learning in strategic situations in which the players have private priors and private information. The author analyses the behaviour of Bayesian rational players both in a repeated game and in a recurrent game when they are uncertain about opponents' behaviour and the game they are playing. The aim of the paper is to explain how Bayesian rational agents learn by playing and to characterize the outcome of this learning process. By studying the concept of 'conjectural equilibrium' and analysing the process of convergence of players' behaviour, the roles played by the notions of merging and of consistency are demonstrated.