Teaching Your Computer to Play Chess (Part 1): Markov Games and TD Learning
2026-04-24 16:00 - 17:00 (Asia/Kolkata) | A201
Speaker: Aakash Ghosh (TIFR)

Abstract:
How do we mathematically formulate the problem of learning to play a game as complex as chess? In the first part of this two-part series, we will approach chess through the lens of Reinforcement Learning and Stochastic Approximation. We begin by formalizing the game as a two-player zero-sum Markov Decision Process, discussing the Bellman Optimality Equation and minimax equilibria.
