Selecting efficient correlated equilibria through distributed learning

A learning rule is completely uncoupled if each player's behavior is conditioned only on his own realized payoffs, and does not need to know the actions or payoffs of anyone else. We demonstrate a simple, completely uncoupled learning rule such that, in any finite normal form game with generic payoffs, the players' realized strategies implements a Pareto optimal coarse correlated (Hannan) equilibrium a very high proportion of the time. A variant of the rule implements correlated equilibrium a very high proportion of the time.