Ohio State nav bar

Provably convergent quasistatic dynamics for mean-field two-player zero-sum games

Computational Mathematics Seminar
January 20, 2022
2:00PM - 3:00PM
Zoom

Date Range
Add to Calendar 2022-01-20 14:00:00 2022-01-20 15:00:00 Provably convergent quasistatic dynamics for mean-field two-player zero-sum games Title:  Provably convergent quasistatic dynamics for mean-field two-player zero-sum games Speaker:  Lexing Ying (Stanford University) Speaker's URL:  https://web.stanford.edu/~lexing/ Abstract:  We study the minimax problem arising from finding the mixed Nash equilibrium for mean-field two-player zero-sum games. Solving this problem requires optimizing over two probability distributions. We consider a quasistatic Wasserstein gradient flow dynamics in which one probability distribution follows the Wasserstein gradient flow, while the other one is always at the equilibrium. Theoretical analysis are conducted on this dynamics, showing its convergence to the mixed Nash equilibrium under mild conditions. Inspired by the continuous dynamics of probability distributions, we derive a quasistatic Langevin gradient descent method with inner-outer iterations, and test the method on different problems, including training mixture of GANs. URL associated with Seminar:  https://people.math.osu.edu/xing.205/seminar.html  Zoom: https://osu.zoom.us/j/99118833389?pwd=UHc4a2o3VnJUZUdRK08xZ1p5clZXUT09 Zoom Department of Mathematics math@osu.edu America/New_York public

Title:  Provably convergent quasistatic dynamics for mean-field two-player zero-sum games

Speaker:  Lexing Ying (Stanford University)

Speaker's URL:  https://web.stanford.edu/~lexing/

Abstract:  We study the minimax problem arising from finding the mixed Nash equilibrium for mean-field two-player zero-sum games. Solving this problem requires optimizing over two probability distributions. We consider a quasistatic Wasserstein gradient flow dynamics in which one probability distribution follows the Wasserstein gradient flow, while the other one is always at the equilibrium. Theoretical analysis are conducted on this dynamics, showing its convergence to the mixed Nash equilibrium under mild conditions. Inspired by the continuous dynamics of probability distributions, we derive a quasistatic Langevin gradient descent method with inner-outer iterations, and test the method on different problems, including training mixture of GANs.

URL associated with Seminar:  https://people.math.osu.edu/xing.205/seminar.html

 Zoom: https://osu.zoom.us/j/99118833389?pwd=UHc4a2o3VnJUZUdRK08xZ1p5clZXUT09

Events Filters: