Fall 2023 GRASP SFI - Samuel Sokota, Carnegie Mellon University

“Reinforcement Learning in Two-Player Zero-Sum Games”
ABSTRACT
I’ll discuss reinforcement learning in two-player zero-sum games. Historically, this area has lacked algorithms that perform well in large settings with imperfect information. I’ll describe a resolution for making self-play RL performant.
PRESENTER
Samuel Sokota is a PhD student at Carnegie Mellon University supervised by Zico Kolter.