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

IF 2.7 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2024-12-01 DOI:10.1063/5.0230729
Piyush Grover, Mandy Huo
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引用次数: 0

Abstract

The framework of mean-field games (MFGs) is used for modeling 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 a 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 traveling wave solution. Our work provides a game-theoretic perspective to the problem of collective motion in non-equilibrium biological and bio-inspired systems.

惯性自行式智能体的平均场动力学博弈模型中的相变。
采用平均场博弈框架对非合作决策主体群体的集体动力学进行建模。我们制定并分析了一个具有惯性动力学和有限范围相互作用的非合作移动智能体相互作用系统的动力学MFG模型,其中每个智能体都最小化生物启发的成本函数。通过分析非线性Fokker-Planck方程和Hamilton-Jacobi-Bellman方程时间系统的前后耦合,得到了平均速度非零的有序状态对应的空间齐次MFG平衡的闭环线性稳定性条件。通过分析和数值模拟的结合,我们表明,当控制的能量成本降低到临界值以下时,该平衡失去稳定性,系统过渡到行波解。我们的工作为非平衡生物和生物启发系统中的集体运动问题提供了博弈论的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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