Framework for adjudicating a chess match with Computer Agents. A pair programming effort with Joyce Lee
- Minimax implemented, capable of evaluating material exclusively
- passes promotion test
in root directory run the following command to start a random game
python3 chengine/main.py
to run tests
python3 chengine/main.py comptest
Post module change
python3 -m chengine.main
python3 -m chengine.main.runtest
python3 -m chengine.tests.runtestGame is adjudicated in chengine/main.py
Players (agents) are located in chengine/players.
To add a new player, make a new folder within players
To activate macOS/Linux, use the command: source env_name/bin/activate
To activate Windows, use the command: env_name\Scripts\activate
Read this to create using VSCode
The following must be done inside the virtual environment
To update the requirements do the following command: pip freeze > requirements.txt
To install from requirements do the following: pip install -r requirements.txt
1.1 - new testing framework and bugfix 1.2 - alpha beta pruning 1.3 - changed top level to use pruning. Added best continuation tracker 1.4 - added late move reduction 1.4.1 - changed late move reduction to prioritise queen promotion 1.5 - added new evaluation function that combines different heuristics. Added pawn occupation heuristic 1.5.1 - added preprocessing step to convert fen into matrix 1.6 - added temporal advantage including a to-move bonus and piece development heuristic 1.7 - added king safety heuristics
Minimax
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Satisfy Checkmate tests
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Evaluate positional advantage
Beyond
- Neural Network Solution