Closed-loop convergence for mean field games with common noise

TL;DR

This paper establishes the convergence of closed-loop approximate equilibria in n-player mean field games with common noise to a well-defined weak mean field equilibrium, extending prior results and accommodating more general conditions.

Contribution

It introduces a new notion of weak mean field equilibria that captures all subsequential limits and proves their equivalence to limits of n-player approximate equilibria under broader strategy classes.

Findings

Weak mean field equilibria capture all subsequential limits.

Every weak mean field equilibrium is a limit of n-player approximate equilibria.

Results extend to unbounded coefficients and non-i.i.d. initial conditions.

Abstract

This paper studies the convergence problem for mean field games with common noise. We define a suitable notion of weak mean field equilibria, which we prove captures all subsequential limit points, as $n\to\infty$, of closed-loop approximate equilibria from the corresponding $n$-player games. This extends to the common noise setting a recent result of the first author, while also simplifying a key step in the proof and allowing unbounded coefficients and non-i.i.d. initial conditions. Conversely, we show that every weak mean field equilibrium arises as the limit of some sequence of approximate equilibria for the $n$-player games, as long as the latter are formulated over a broader class of closed-loop strategies which may depend on an additional common signal.