Case study · 2022
[Case Study]
Chess AI
Fully functional chess game with an AI with alpha-beta pruning.
Overview
Problem
Minimax is intuitive on paper. Alpha-beta pruning is the part that always felt magical.
Approach
Built the engine in pure Python: bitboard-style representation, move generation, alpha-beta with iterative deepening, and a positional eval function.
Outcome
It plays a respectable game — and the algorithm finally feels intuitive.
Outcome
A playable engine that beats casual players and made the algorithms click.