This is a Fall 2020 Deep Learning Final Project.
The repo consists of player, state, and a Jupyter notebook to interpret the result.
Some of the result can be found in the "League_result" folder, where different agents play against each other.
State package contains all three different States, the normal TTT, superposition TTT, and the quantum TTT.
Player pacakge contains different players under different states, include agent, random player and human players.
model.py contains the models used in the experiment, including linear models and multiple neural networks.
demo.ipynb contains the version we trail we run to analyze performance.
Group Stage.ipynb contains the necessary steps to run the group stage experiment