In this paper, we provide a theoretical prediction of the way in which adaptive players behave in the long run in normal form games with strict Nash equilibria. In the model, each player assigns subjective payoff assessments to his own actions, where the assessment of each action is a weighted...

In this paper, we provide a theoretical prediction of the way in which adaptive players behave in the long run in normal form games with strict Nash equilibria. In the model, each player assigns subjective payoff assessments to his own actions, where the assessment of each action is a weighted...

This paper studies the reinforcement learning of Erev and Roth with foregone payoff information in normal form games: players observe not only the realised payoffs but also foregone payoffs, the ones which they could have obtained if they had chosen the other actions. We provide conditions under...

This paper investigates the way in which adaptive players behave in the long run in finitely repeated games. Each player assigns subjective payoff assessments to his own actions and chooses the action which has the highest assessment at each of his information sets. After receiving payoffs,...

In this paper, we investigate the condition under which players of an adaptive learning model, including the one of stochastic fictitious play learning, learn to follow a logit quantal response equilibrium corresponding to a strict Nash equilibrium, the one which approaches the Nash equilibrium...

In this paper, we provide a theoretical prediction of the way in which adaptive players behave in the long run in games with strict Nash equilibria. In the model, each player picks the action which has the highest assessment, which is a weighted average of past payoffs. Each player updates his...

In this paper, we provide a theoretical prediction of the way in which adaptive players behave in the long run in normal form games with strict Nash equilibria. In the model, each player assigns subjective payoff assessments to his own actions, where the assessment of each action is a weighted...