Open-Loop and Closed-Loop Strategies for Linear Quadratic Mean Field Games: The Direct Approach

Fuente: arXiv
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Autori principali: Liang, Yong, Wang, Bing-Chang, Zhang, Huanshui
Natura: Preprint
Pubblicazione: 2025
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author Liang, Yong
Wang, Bing-Chang
Zhang, Huanshui
author_facet Liang, Yong
Wang, Bing-Chang
Zhang, Huanshui
contents This paper delves into studying the differences and connections between open-loop and closed-loop strategies for the linear quadratic (LQ) mean field games (MFGs) by the direct approach. The investigation begins with the finite-population system for solving the solvability of open-loop and closed-loop systems within a unified framework under the global information pattern. By a comprehensive analysis through variational methods, the necessary and sufficient conditions are obtained for the existence of centralized open-loop and closed-loop Nash equilibria, which are characterized by the solvability of a system of forward-backward stochastic differential equations and a system of Riccati equations, respectively. The connections and disparities between centralized open-loop and closed-loop Nash equilibria are analyzed. Then, the decentralized control is designed by studying the asymptotic solvability for both open-loop and closed-loop systems. Asymptotically decentralized Nash equilibria are obtained by considering the centralized open-loop and closed-loop Nash equilibria in the infinite-population system, which requires a standard and an asymmetric Riccati equations. The results demonstrate that divergences between the centralized open-loop and closed-loop Nash equilibria in the finite-population system, but the corresponding asymptotically decentralized Nash equilibria in the infinite-population system are consistent. Therefore, the choice of open-loop and closed-loop strategies does not play an essential role in the design of decentralized control for LQ MFGs.
format Preprint
id arxiv_https___arxiv_org_abs_2504_13496
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Open-Loop and Closed-Loop Strategies for Linear Quadratic Mean Field Games: The Direct Approach
Liang, Yong
Wang, Bing-Chang
Zhang, Huanshui
Optimization and Control
This paper delves into studying the differences and connections between open-loop and closed-loop strategies for the linear quadratic (LQ) mean field games (MFGs) by the direct approach. The investigation begins with the finite-population system for solving the solvability of open-loop and closed-loop systems within a unified framework under the global information pattern. By a comprehensive analysis through variational methods, the necessary and sufficient conditions are obtained for the existence of centralized open-loop and closed-loop Nash equilibria, which are characterized by the solvability of a system of forward-backward stochastic differential equations and a system of Riccati equations, respectively. The connections and disparities between centralized open-loop and closed-loop Nash equilibria are analyzed. Then, the decentralized control is designed by studying the asymptotic solvability for both open-loop and closed-loop systems. Asymptotically decentralized Nash equilibria are obtained by considering the centralized open-loop and closed-loop Nash equilibria in the infinite-population system, which requires a standard and an asymmetric Riccati equations. The results demonstrate that divergences between the centralized open-loop and closed-loop Nash equilibria in the finite-population system, but the corresponding asymptotically decentralized Nash equilibria in the infinite-population system are consistent. Therefore, the choice of open-loop and closed-loop strategies does not play an essential role in the design of decentralized control for LQ MFGs.
title Open-Loop and Closed-Loop Strategies for Linear Quadratic Mean Field Games: The Direct Approach
topic Optimization and Control
url https://arxiv.org/abs/2504.13496