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[报告]Mean Field Game Theory and Application to a Stochastic Growth Model

作者:admin  发布时间:2015年07月02日 12:49  点击:


报告题目: Mean Field Game Theory and Application to a Stochastic Growth Model

主讲人:黄民懿 , School of Mathematics and Statistics, Carleton University

时间:2015年7月6日上午10:00-11:00

地点:延长校区电机楼2楼会议室

报告摘要:This talk will start by a brief overview of non-cooperative games and related mathematical tools.  We then continue to describe mean field game theory. This area has wide  applications to communication networks, power systems, economics and finance, public health, among others. Our basic modeling  involves weakly coupled diffusions as the dynamics of a large number of decision makers. The idea of consistent mean field  approximations  will be explained. Except linear-quadratic-Gaussian (LQG) and linear-exponential-quadratic-Gaussian (LEQG) models, explicit solutions are rare in mean field games. This talk will identify a new class of mean field game  models which have an economic background and allow closed-form solutions. This is a joint work with S. L. Nguyen.        

报告人简介: Minyi Huang received  his Ph.D. from McGill University in 2003. He is now with Carleton University, Ottawa, where he is an  Associate Professor in the School of Mathematics and Statistics. His research interests include mean field stochastic control and dynamic games, multi-agent control and computation in distributed networks with applications. He is one of the original contributors of mean field game theory.

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