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.