Convergence of the equilibrium measure for LQG mean field games with common noise
滨苍蹿辞谤尘补濒听厂测蝉迟别尘蝉听厂别尘颈苍补谤听(滨厂厂)
Centre听for听Intelligent听Machines听(CIM)听and听Groupe听d'Etudes听et听de Recherche听en听Analyse听des听Decisions听(GERAD)
Speaker: Jiamin Jian
惭别别迟颈苍驳听滨顿:听845听1388听1004听听听听听听听
笔补蝉蝉肠辞诲别:听痴滨厂厂
Abstract:
This work focuses on exploring the convergence properties of a generic player鈥檚 trajectory and empirical measures in an N-player Linear-Quadratic-Gaussian Nash game, where Brownian motion serves as the common noise. We establish three distinct convergence rates concerning the representative player and empirical measure. To investigate the convergence, the methodology relies on a specific decomposition of the equilibrium path in the N-player game and utilizes the associated mean field game framework. It is a joint work with Prof. Qingshuo Song and Dr. Jiaxuan Ye.
Bio:
Jiamin Jian is a Ph.D. candidate in Department of Mathematical sciences at Worcester Polytechnic Institute under the supervision of Prof. Qingshuo Song. His research interest includes stochastic control, mean field games and financial mathematics. Before that, He got the Master鈥檚 degree in Mathematical Finance and Statistics from City University of Hong Kong in 2019 and the Bachelor鈥檚 degrees in Mathematics and Applied Mathematics from Nankai University in 2018.
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