Learning Correlated Equilibria in Mean-Field Games. (arXiv:2208.10138v1 [cs.GT])

The designs of many large-scale systems today, from traffic routing
environments to smart grids, rely on game-theoretic equilibrium concepts.
However, as the size of an $N$-player game typically grows exponentially with
$N$, standard game theoretic analysis becomes effectively infeasible beyond a
low number of players. Recent approaches have gone around this limitation by
instead considering Mean-Field games, an approximation of anonymous $N$-player
games, where the number of players is infinite and the population's state
distribution, instead of every individual player's …

arxiv equilibria games learning mean