We investigate in a laboratory setting whether revealing information on intelligence affects behavior in games with repeated interactions. In our experimental design we communicate information on the cognitive ability of both players. We use three stage games: Prisoners’ Dilemma (PD) and two...

Under the assumption that individuals know the conditional distributions of signals given the payoff-relevant parameters, existing results conclude that as individuals observe infinitely many signals, their beliefs about the parameters will eventually merge. We first show that these results are...

Predictions under common knowledge of payoffs may differ from those under arbitrarily, but finitely, many orders of mutual knowledge; Rubinstein's (1989)Email game is a seminal example. Weinstein and Yildiz (2007) showed that the discontinuity in the example generalizes: for all types with...

Restricting attention to economic environments, we study implementation under perturbed better-response dynamics (BRD). A social choice function (SCF) is implementable in stochastically stable strategies of perturbed BRD whenever the only outcome supported by the stochastically stable strategies...

We show that essentially every communication equilibrium of any finite Bayesian game with two players can be implemented as a strategic form correlated equilibrium of an extended game, in which before choosing actions as in the Bayesian game, the players engage in a possibly infinitely long (but...

The Nash program is an important research agenda initiated in Nash (Econometrica 21:128-140, 1953) in order to bridge the gap between the noncooperative and cooperative counterparts of game theory. The program is thus turning sixty-seven years old, but I will argue it is not ready for...

This paper provides a simple theoretical framework to evaluate the effect of key parameters of ranking algorithms, namely popularity and personalization parameters, on measures of platform engagement, misinformation and polarization. The results show that an increase in the weight assigned to...

Bayesian updating is the dominant theory of learning. However, the theory is silent about how individuals react to events that were previously unforeseeable or unforeseen. Building on a recently developed axiomatic framework to analyze such situations, we test if subjects update their beliefs...