Topological bifurcations in a mean-field game

TL;DR

This paper investigates the complex bifurcation structures in mean-field games using a reduced-order model focused on the first two moments of the agent distribution, revealing topological features that influence solution behaviors.

Contribution

The study introduces a reduced-order model for finite-time MFGs and uncovers topological bifurcation structures through phase space analysis, linking invariant manifolds to solution branches.

Findings

Invariant manifolds influence bifurcation diagrams

Topological signatures characterize solution branches

Qualitative agreement with full PDE system results

Abstract

Mean-field games (MFG) provide a statistical physics inspired modeling framework for decision making in large-populations of strategic, non-cooperative agents. Mathematically, these systems consist of a forward-backward in time system of two coupled nonlinear partial differential equations (PDEs), namely the Fokker-Plank and the Hamilton-Jacobi-Bellman equations, governing the agent state and control distribution, respectively. In this work, we study a finite-time MFG with a rich global bifurcation structure using a reduced-order model (ROM). The ROM is a 4D two-point boundary value problem obtained by restricting the controlled dynamics to first two moments of the agent state distribution, i.e., the mean and the variance. Phase space analysis of the ROM reveals that the invariant manifolds of periodic orbits around the so-called `ergodic MFG equilibrium' play a crucial role in determining the bifurcation diagram, and impart a topological signature to various solution branches. We show a qualitative agreement of these results with numerical solutions of the full-order MFG PDE system.