This paper introduces epsilon-stability as a generalization of the concept of stochastic stability in learning and evolutionary game dynamics. An outcome of a model of stochastic evolutionary dynamics is said to be epsilon-stable in the long-run if for a given model of mistakes it maximizes its...

Learning and stochastic evolutionary models provide a useful framework for analyzing repeated interactions and experimentation among economic agents over time. They also provide sharp predictions about equilibrium selection when multiplicity exists. This paper defines three convergence measures,...