Phase transition in a kinetic mean-field game model of inertial self-propelled agents

TL;DR

This paper investigates a kinetic mean-field game model for inertial self-propelled agents, revealing a phase transition from an ordered state to traveling waves as control costs decrease, with implications for biological collective motion.

Contribution

It introduces a kinetic MFG model with inertial dynamics and finite-range interactions, analyzing stability and phase transitions in collective motion.

Findings

Ordered equilibrium loses stability below a critical control cost.

System transitions to traveling wave solutions at critical point.

Provides a game-theoretic framework for biological collective motion.

Abstract

The framework of Mean-field Games (MFGs) is used for modelling the collective dynamics of large populations of non-cooperative decision-making agents. We formulate and analyze a kinetic MFG model for an interacting system of non-cooperative motile agents with inertial dynamics and finite-range interactions, where each agent is minimizing a biologically inspired cost function. By analyzing the associated coupled forward-backward in time system of nonlinear Fokker-Planck and Hamilton-Jacobi-Bellman equations, we obtain conditions for closed-loop linear stability of the spatially homogeneous MFG equilibrium that corresponds to an ordered state with non-zero mean speed. Using a combination of analysis and numerical simulations, we show that when energetic cost of control is reduced below a critical value, this equilibrium loses stability, and the system transitions to a travelling wave solution. Our work provides a game-theoretic perspective to the problem of collective motion in non-equilibrium biological and bio-inspired systems.