We show that the playing sequence-the order in which players update their actions-is a crucial determinant of whether the best-response dynamic converges to a Nash equilibrium. Specifically, we analyze the probability that the best-response dynamic converges to a pure Nash equilibrium in random...

In John Nash’s proofs for the existence of (Nash) equilibria based on Brouwer’s theorem, an iteration mapping is used. A continuous- time analogue of the same mapping has been studied even earlier by Brown and von Neumann. This differential equation has recently been suggested as a plausible...

We study the design of mechanisms that implement Lindahl or Walrasian allocations and whose Nash equilibria are dynamically stable for a wide class of adaptive dynamics. We argue that supermodularity is not a desirable stability criterion in this mechanism design context, focusing instead on...

Do boundedly rational players learn to choose equilibrium strategies as they play a game repeatedly? A large literature in behavioral game theory has proposed and experimentally tested various learning algorithms, but a comparative analysis of their equilibrium convergence properties is lacking....

The new learning dynamic of Brown, von Neuman and Nash (1950) is introduced to macroeconomic dynamics via the cobweb model with rational and naive forecasting strategies. This dynamic has appealing properties such as positive correlation and inventiveness. There is persistent heterogeneity in...

We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The “TASP” (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under fictitious play like learning processes....

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 apply the dynamic stochastic framework proposed by recent evolutionaryliterature to the class of strict supermodular games when two simplebehavior rules coexist in the population, imitation and myopic optimization.We assume that myopic optimizers are able to see how well their payoff...

The novelty of our model is to combine models of collective action on networks with models of social learning. Agents are connected according to an undirected graph, the social network, and have the choice between two actions: either to adopt a new behavior or technology or stay with the default...

In a coordination game such as the Battle of the Sexes, agents can condition their plays on external signals that can, in theory, lead to a Correlated Equilibrium that can improve the overall payoffs of the agents. Here we explore whether boundedly rational, adaptive agents can learn to...