No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix

As such, several crucial questions arise: What are the game-theoretic implications of the no-regret guarantees of FTRL? Do the dynamics of FTRL converge to an equilibrium of the underlying game? A folk answer to this question is that " no-regret learning converges to equilibrium in all games "