Using Reinforcement Learning to Play Mario

Using the stable-baselines library, we used three different RL algorithms (Deep Q Network, Synchronous Actor Critic, Proximal Policy Optimization) to teach an agent to complete the first level of Mario.

Must use python 3.7 and pip install requirements.txt. Run train.py first to train models, then run main.py to work with the trained models.