Overview
An exploration of reinforcement learning through Othello, using an AlphaZero-inspired approach to learning game-playing behavior.
Architecture / Methods
The project explores neural-network-guided Monte Carlo Tree Search and self-play using Python and PyTorch. Othello provides a bounded setting for investigating the relationship between learned guidance, search, and decision-making.