A population of agents recurrently plays a two-strategy population game. When an agent receives a revision opportunity, he chooses a new strategy using a noisy best response rule that satisfies mild regularity conditions; best response with mu-tations, logit choice, and probit choice are all permitted. We study the long run behavior of the resulting Markov process when the noise level η is small and the population size N is large. We obtain a precise characterization of the asymptot-ics of the stationary distributions μNη as η approaches zero and N approaches infinity, and we establish that these asymptotics are the same for either order of limits and for all simultaneous limits. In general, different noisy best response rules can generate ...