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 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...

This chapter reviews recent experimental data testing game theory and behavioral models that have been inspired to explain those data. The models fall into four groups: in cognitive hierarchy or level- k models, the assumption of equilibrium is relaxed by assuming agents have beliefs about other...