This chapter describes a very general approach to learning in games: experience-weighted attraction (EWA) learning. This approach strives to explain, for every choice in an experiment, how that choice arose from players' previous behavior and experience, using a general model which can be...

We apply Camerer and Ho's experience-weighted attraction (EWA) model of learning to extensive-form signaling games. Since these games often have many equilibria, logical 'refinements' have been used to predict which equilibrium will occur. Brandts and Holt conjectured that belief formation could...

This paper describes a parametric approach to weakening rationality assumptions in game theory to fit empirical data better. The central features of game theory are: The concept of a game (players, strategies, information, timing, outcomes); strategic thinking; mutual consistency of beliefs and...