English

On Time-Inconsistency in Mean Field Games

Optimization and Control 2024-09-13 v2 Computer Science and Game Theory Probability

Abstract

We investigate an infinite-horizon time-inconsistent mean-field game (MFG) in a discrete time setting. We first present a classic equilibrium for the MFG and its associated existence result. This classic equilibrium aligns with the conventional equilibrium concept studied in MFG literature when the context is time-consistent. Then we demonstrate that while this equilibrium produces an approximate optimal strategy when applied to the related NN-agent games, it does so solely in a precommitment sense. Therefore, it cannot function as a genuinely approximate equilibrium strategy from the perspective of a sophisticated agent within the NN-agent game. To address this limitation, we propose a new consistent equilibrium concept in both the MFG and the NN-agent game. We show that a consistent equilibrium in the MFG can indeed function as an approximate consistent equilibrium in the NN-agent game. Additionally, we analyze the convergence of consistent equilibria for NN-agent games toward a consistent MFG equilibrium as NN tends to infinity.

Keywords

Cite

@article{arxiv.2312.07770,
  title  = {On Time-Inconsistency in Mean Field Games},
  author = {Erhan Bayraktar and Zhenhua Wang},
  journal= {arXiv preprint arXiv:2312.07770},
  year   = {2024}
}
R2 v1 2026-06-28T13:49:08.299Z