♘♗♖♕♔ Abadejo-Chess ♚♛♜♝♞

A Neural Chess AI in Python

♙ Description

This aims to be a simple and inefficient chess engine programed in Python for learning about AI, PyTorch and dataset generation

♙ Usage

Run app.py with Python3, it works using flask on localhost, go to http://127.0.0.1:5000/ for the move interface

• Simply drag the piece to the desired square, ilegal moves are rejected, promoting to queen is automatic, followed autmatically by an enemy computer move or:
• Human move: Makes the SAN notated move followed autmatically by an enemy computer move
• Computer move: Makes a move using the engine for the side currently playing

♙ Dependencies

Python 3 of course

• chess: A lifesaver, probably wouldn't have started the projet w/o this
• numpy: Efficient data structures
• flask: Interface

optional:

• PyTorch: Neural evaluation (use pip, the conda version is too old)
• cProfile and snakeviz: for profiling to optimize a little more

♙ Objetives

• Make a chess engine that can beat me 😎
• Use a CNN for eval
• Learn more about PyTorch and dataset generation

♙ TODO

• User input via clicking
• Info in the webpage
• NegaMax
• NegaMax + Zobrist Hash with alpha beta pruning
• Iterative deepening
• Aspiration Window
• Negascout (Principal variation search)
• Pypy (Pypy 3.7 seems 1% to 10% slower than Python 3.8)
• Piece value heuristic
• MiniMax
• Board rendering
• Movility to the heuristic
• MiniMax + Alpha Beta pruning
• Piece square tables
• Move ordering (moves that capture pieces may be examined before moves that do not, and moves that have scored highly in earlier passes through the game-tree analysis may be evaluated before others)
• Quiescence search
• User input via submit field
• Automatic enemy move
• Zobrist Hashing
• Tranposition tables
• Neural network evaluation