Alphazero for 6-6-4 Tictactoe

Implementation of alphazero learning algorithm for 6-6-4 Tictactoe

Trained Alphazero agent vs human!

The trained alphazero agent easily defeated me!

alphazero_tictactoe.ipynb: Jupyter notebook for training alphazero for normal 3x3x3 tictactoe
alphazero_tictactoe_advanced.ipynb: Jupyter notebook for training alphazero for complex 6x6x4 tictactoe
MCTS.py: Helper file for Monte Carlo Tree Search
Play.py: File for helping with interactive game play
ConnectN.py: File defining the game structure
6-6-4-pie.policy: Trained policy weights for 6x6x4 tictactoe

Follow the step by step instructions in alphazero_tictactoe_advanced.ipynb to train your own alphazero agent!

Name		Name	Last commit message	Last commit date
Latest commit History 21 Commits
.ipynb_checkpoints		.ipynb_checkpoints
__pycache__		__pycache__
images		images
.gitignore		.gitignore
6-6-4-pie-0.mypolicy		6-6-4-pie-0.mypolicy
6-6-4-pie-1000.mypolicy		6-6-4-pie-1000.mypolicy
6-6-4-pie-1500.mypolicy		6-6-4-pie-1500.mypolicy
6-6-4-pie-2000.mypolicy		6-6-4-pie-2000.mypolicy
6-6-4-pie-500.mypolicy		6-6-4-pie-500.mypolicy
6-6-4-pie.policy		6-6-4-pie.policy
ConnectN.py		ConnectN.py
LICENSE		LICENSE
MCTS.py		MCTS.py
Play.py		Play.py
README.md		README.md
alphazero-TicTacToe-advanced.ipynb		alphazero-TicTacToe-advanced.ipynb
alphazero-TicTacToe.ipynb		alphazero-TicTacToe.ipynb