Selection by vanishing common noise for potential finite state mean field games
Alekos Cecchin, Fran\c{c}ois Delarue

TL;DR
This paper introduces a selection principle for potential mean field games on finite state spaces by using a vanishing common noise approach, ensuring unique solvability and linking solutions to a mean field control problem.
Contribution
It develops a vanishing viscosity method with common noise to select unique potential solutions in finite state mean field games, connecting them to control problems.
Findings
Unique solvability of mean field games with common noise
Convergence of viscous master equation solutions to control problem solutions
Establishment of an intrinsic uniqueness criterion
Abstract
The goal of this paper is to provide a selection principle for potential mean field games on a finite state space and, in this respect, to show that equilibria that do not minimize the corresponding mean field control problem should be ruled out. Our strategy is a tailored-made version of the vanishing viscosity method for partial differential equations. Here, the viscosity has to be understood as the square intensity of a common noise that is inserted in the mean field game or, equivalently, as the diffusivity parameter in the related parabolic version of the master equation. As established recently, the randomly forced mean field game becomes indeed uniquely solvable for a relevant choice of a Wright-Fisher common noise, the counterpart of which in the master equation is a Kimura operator on the simplex. We here elaborate on this idea to make the mean field game with common noise both…
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