We study the evolution of strategic psychological capabilities in a population of interacting agents. Specifically,we consider agentswhich are either blind orwithmindsight, and either transparent or opaque. An agent with mindsight can observe the psychological makeup of a transparent agent,...

We show that local potential maximizer (\cite{morris+05}) with constant weights is stochastically stable in the log-linear dynamics provided that the payoff function or the associated local potential function is supermodular. We illustrate and discuss, through a series of examples, the use of...

We propose a learning dynamic with agents using samples of past play to estimate the distribution of other players' strategy choices and best responding to this estimate. To account for noisy play, estimated distributions over other players' strategy choices have full support in the other...

We consider a model of stochastic evolution under general noisy best response protocols, allowing the probabilities of suboptimal choices to depend on their payoff consequences. Our analysis focuses on behavior in the small noise double limit: we first take the noise level in agents' decisions...

This paper studies infinite-horizon stochastic games in which players observe payoffs and noisy public information about a hidden state each period. We find that, very generally, the feasible and individually rational payoff set is invariant to the initial prior about the state in the limit as...