We analyze a population game as being constituted by a set of players, a normal form game and an interaction pattern. The latter specifies the way players are repeatedly matched in the population to play one shot of the normal form game. We first relate the set of equilibria of the populations game to the set of correlated equilibria of the underlying game, and then focus on learning processes that we model as Markovian adaptive dynamics. For the class of doubly symmetric games, we formulate general conditions under which convergence is obtained under myopic best-reply dynamics. We also analyze noisy best-reply dynamics, where players' behaviour is perturbed by payoff dependent mistakes, and explicitly characterize the ergodic distribution of the population game in terms of the correlated equilibrium payoffs of the underlying game. We conclude with ome good examples.
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