Model-free DQN learning achieves suboptimality bounds of O(1/sqrt(Ns)) + O(1/N) in Karma DPGs at equilibrium, and deep RL combined with fictitious play empirically reaches near-Stationary Nash Equilibrium from scratch.
Mean field games.Japanese journal of mathematics, 2(1):229–260
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Forward relative performance processes with CRRA wealth utility and separable time-space dependence necessarily induce matching CRRA consumption utility, yielding closed-form Nash equilibria for n-player and mean-field games with consumption.
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