This paper defines regular and weakly regular equilibria for monotone Bayesian games with one-dimensional actions and types.  It proves an index theorem and provides applications to uniqueness of equilibrium.  It also provides analyses of stability with respect to perturbations and dynamic...

This paper presents a neural network model developed to simulate the endogenous emergence of bounded-rational behavior in normal-form games. There exists an algorithm which, if learnt by a neural network, would enable it to perfectly select Nash equilibria in never before seen games. However,...

In the context of a "beauty contest" coordination game (in which pay-offs depend on the proximity of actions to an unobserved state variable and to the average action) players choose how much costly attention to pay to various informative signals; they endogenously select information sources and...

This paper considers a simple adaptive learning rule in Bayesian games where players employ threshold strategies. Global convergence results are given for supermodular games and potentital games.

The experiment presented in this paper employs 3 x 3 games to analyze how perception of a game affects behavior in the presence or absence of a minimal framing effect and of uncertainty about the values of some game payoffs. We vary the harmony of practice stage games, and explain how this...

In the context of macroeconomic coordination, studies of the social value of information distinguish sharply between private and public information.  However, no information is truly public (that is, common knowledge) or private in the established sense.  This paper develops a general approach...

This paper studies learning in monotone Bayesian games with one-dimensional types and finitely many actions. Players switch between actions at a set of thresholds.  A learning algorithm under which players adjust their strategies in the direction of better ones using payoffs received at...

This paper examines the convergence of payoffs and strategies in Erev and Roth`s model of reinforcement learning. When all players use this rule it eliminates iteratively dominated strategies and in two-person constant-sum games average payoffs converge to the value of the game. Strategies...

People believe that, even in very large samples, proportions of binary signals might depart significantly from the population mean.  We model this "non-belief in the Law of Large Numbers" by assuming that a person believes that proportions in any given sample might be determined by a rate...

The diffusion of an innovation can be represented by a process in which agents choose perturbed best responses to what their neighbors are currently doing.  Diffusion is said to be fast if the expected waiting time until the innovation spreads widely is bounded above independently of the size...