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ISS Informal Systems Seminar

Convergence of the equilibrium measure for LQG mean field games with common noise

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Feb 16, 2024   10:30 AM — 11:30 AM

Jiamin Jian Worcester Polytechnic Institute, United States

Jiamin Jian

This work focuses on exploring the convergence properties of a generic player’s 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’s degree in Mathematical Finance and Statistics from City University of Hong Kong in 2019 and the Bachelor’s degrees in Mathematics and Applied Mathematics from Nankai University in 2018.

Peter E. Caines organizer
Aditya Mahajan organizer
Shuang Gao organizer
Alex Dunyak organizer
Borna Sayedana organizer

Location

Online meeting
Zoom
Montréal Québec
Canada

Associated organization

Centre for intelligent machines (CIM)

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