Abstract:  In this talk, we will discuss how we can utilize deep learning to solve complex (dynamic and stochastic) game theoretical problems where there are many agents (such as banks, companies or people) interacting. We will first look at a stochastic optimal control problem for one agent and explain how we can use deep learning to solve this problem. Later, we will move to the multi-agent setup, and we will discuss and compare two equilibrium notions in game theory: Nash equilibrium and Stackelberg equilibrium. After explaining how a Nash equilibrium can be approximated for dynamic and stochastic games with a large number of agents through mean field games, we will introduce the Stackelberg mean field games between a principal (i.e., regulator) and many agents. Stackelberg mean field game models can be used to find optimal policies for a large group of noncooperative agents with a motivation to model different financial problems such as mitigating the systemic risk with a regulator. We will discuss how (intrinsically bi-level) Stackelberg mean field game model can be rewritten to propose a single-level deep learning method to solve this complex problem. At the end we will illustrate the results of our approach with some financial applications such as systemic risk modeling and optimal contract for many employees.

Bio: Gökçe Dayanıklı is an assistant professor at the University of Illinois Urbana-Champaign, Department of Statistics. Before joining UIUC, she was a term assistant professor of Statistics at Columbia University. She completed her Ph.D. in Operations Research & Financial Engineering at Princeton University where she was awarded the School of Engineering and Applied Sciences Award for Excellence. During Fall 2021, she was a visiting graduate researcher at the Institute for Mathematical and Statistical Innovation (IMSI at University of Chicago) to participate in the "Distributed Solutions to Complex Societal Problems" program.

Meeting Recording: https://ucsb.zoom.us/rec/share/xCBishh9gMonKnrLpjX99gqSArYhFITVm1UfI0WfCV1K73YeTlIJqxw1XFOPytQ.HRF-fI6FVmPs4y0o

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