Dots and Boxes Final Project

Running Project

• Install Requirements from requirements.txt
• python main.py to compete algorithms

Docker Setup (If needed)

For easy environment setup, we can use nvidia-docker. Once you have nvidia-docker set up, we can then simply run:

./setup_env.sh

To set up a (default: pyTorch) Jupyter docker container. We can now open a new terminal and enter:

docker exec -ti pytorch_notebook python main.py

Team Members:

• Jarrett Arredondo
• Colin Mettler
• Chloe Plasse
• Krystal Grant

Credits

• Norelli, A., & Panconesi, A. (2021). OLIVAW: Mastering Othello without Human Knowledge, nor a Fortune. https://doi.org/10.48550/ARXIV.2103.17228
• Costa, G. P. da. (2022). Machine learning methods applied to the dots and boxes board game [M.S., University Of Algarve]. https://sapientia.ualg.pt/handle/10400.1/18772
• Surag Nair: Alpha Zero Framework
• Carlos Aguayo: Dots and Boxes example model (which we expanded from)
• Peters, T. V. (2018). Mastering the game of Dots and Boxes with deep neural networks and tree search [M.S.]. University of Bremen.
• Scenarios: Berlekamp, E. R. (2000). The Dots and Boxes Game: Sophisticated Child’s Play. CRC Press.