LQG Graphon Mean Field Games: Graphon Invariant Subspaces

被引:10
|
作者
Gao, Shuang [1 ]
Caines, Peter E. [1 ]
Huang, Minyi [2 ]
机构
[1] McGill Univ, Dept Elect & Comp Engn, Montreal, PQ, Canada
[2] Carleton Univ, Sch Math & Stat, Ottawa, ON, Canada
来源
2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2021年
基金
加拿大自然科学与工程研究理事会;
关键词
DENSE GRAPHS; CONVERGENT SEQUENCES; SYSTEMS;
D O I
10.1109/CDC45484.2021.9683037
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper studies approximate solutions to largescale linear quadratic stochastic games with homogeneous nodal dynamics and heterogeneous network couplings based on the graphon mean field game framework in [1]-[3]. A graphon time-varying dynamical system model is first formulated to study the limit problem of linear quadratic Gaussian graphon mean field games (LQG-GMFG). The Nash equilibrium to the limit problem is then characterized by two coupled graphon time-varying dynamical systems. Based on this characterization, we establish two sufficient conditions for the existence of a unique solution to the limit LQG-GMFG problem, and moreover we provide a new asymptotic error bound for applications of approximate solutions to finite-network games. Finally, simulation results on random networks are demonstrated
引用
收藏
页码:5253 / 5260
页数:8
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