On Asymptotic Nash Equilibrium for Linear Quadratic Mean-Field Games

Title: On Asymptotic Nash Equilibrium for Linear Quadratic Mean-Field Games
Creator: Li, Zhipeng; Fu, Minyue; Cai, Qianqian
Relation: 17th International Conference on Control, Automation, Robotics and Vision (ICARCV). Proceedings of 17th International Conference on Control, Automation, Robotics and Vision (ICARCV) (SINGAPORE, Singapore 11-13 December 2022) p. 571-575
Relation: ARC.DP200103507 http://purl.org/au-research/grants/arc/DP200103507
Publisher Link: http://dx.doi.org/10.1109/ICARCV57592.2022.10004298
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Resource Type: conference paper
Date: 2022
Description: A new asymptotic Nash equilibrium for a class of linear quadratic mean-field game problem with a finite number of agents is found by using the cost function decomposition method. The cost function value corresponding with this equilibrium is also computed. This value turns out to be smaller than the one obtained by the state average approximation method. The difference is prominent when the number of agents is small, but vanishes as the agents’ number tends to infinity.
Subject: computation theory; game theory; cost function decomposition method; asymptotic; Nash equilibria
Identifier: http://hdl.handle.net/1959.13/1486219
Identifier: uon:51805
Identifier: ISSN:978-166547687-4
Language: eng
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