Mean Field Game and Control for Switching Hybrid Systems

TL;DR

This paper develops mean field game and control strategies for large populations of agents in hybrid systems with switching dynamics, providing scalable solutions for complex, real-world scenarios like emergency evacuations.

Contribution

It introduces a novel framework combining mean field control with hybrid systems, including computational methods for solving the associated integro-PDEs.

Findings

Effective decentralized control in large-scale switching systems

Numerical validation in emergency evacuation scenarios

Scalable solution approach for hybrid mean field games

Abstract

Mean field games and controls involve guiding the behavior of large populations of interacting agents, where each individual's influence on the group is negligible but collectively impacts overall dynamics. Hybrid systems integrate continuous dynamics with discrete transitions, effectively modeling the complex interplay between continuous flows and instantaneous jumps in a unified framework. This paper formulates mean field game and control strategies for switching hybrid systems and proposes computational methods to solve the resulting integro-partial differential equation. This approach enables scalable, decentralized decision-making in large-scale switching systems, which is illustrated through numerical examples in an emergency evacuation scenario with sudden changes in the surrounding environment.