Linear Quadratic Mean-Field Game-Team Analysis: A Mixed Coalition Approach

Jianhui Huang; Zhenghong Qiu; Zeng WU; Shujun Wang

doi:10.1016/j.automatica.2023.111358

Linear Quadratic Mean-Field Game-Team Analysis: A Mixed Coalition Approach

Jianhui Huang, Zhenghong Qiu, Zeng WU, Shujun Wang

Department of Applied Mathematics

Research output: Journal article publication › Journal article › Academic research › peer-review

1 Citation (Scopus)

Abstract

Mean-field theory has been extensively explored in decision analysis of large-scale (LS) systems but traditionally in "pure" cooperative or competitive settings. This leads to the so-called mean-field game (MG) or mean-field team (MT). This paper introduces a new class of LS systems with cooperative inner layer and competitive outer layer, so a "mixed" mean-field analysis is proposed for distributed game-team strategy. A novel asymptotic mixed-equilibrium-optima is also proposed and verified.

Original language	English
Article number	111358
Pages (from-to)	1-8
Number of pages	8
Journal	Automatica
Volume	159
DOIs	https://doi.org/10.1016/j.automatica.2023.111358
Publication status	Published - Jan 2024

Keywords

Mean-field game
Mean-field team
Game-team mixed strategy
Mixed-equilibrium-optima

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10.1016/j.automatica.2023.111358

Cite this

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KW - Mixed-equilibrium-optima

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JO - Automatica

JF - Automatica

M1 - 111358

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Linear Quadratic Mean-Field Game-Team Analysis: A Mixed Coalition Approach

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