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

Webinaire : Convergence of the equilibrium measure for LQG mean field games with common noise
Séminaire informel de théorie des systèmes (ISS)

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

16 février 2024   10 h 30 — 11 h 30

Jiamin Jian Worcester Polytechnic Institute, États-Unis

Lien pour le webinaire sur Zoom.

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.

Date

Vendredi 16 février 2024
Débute à 10h30

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Gratuit

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