This project implements a reinforcement learning agent that learns to play Super Mario Bros using the PPO algorithm from the Stable Baselines3 library. The environment is provided by the gym_super_mario_bros library.
To run this project, you will need to install the following dependencies:
- Python 3.6 or higher
- gym_super_mario_bros
- stable-baselines3
- nes_py
- torch
- torchvision
- torchaudio
You can install the dependencies using the following commands:
!pip3 install torch torchvision torchaudio
!pip install gym_super_mario_bros stable-baselines3[extra] nes_py
To run the Super Mario RL agent, simply execute the model.py script:
python model.py
This will train the agent for 5000 steps and then render the environment as the agent plays. You can modify the number of training steps by changing the total_timesteps parameter in the model.learn() function call.
This project was inspired by the article "Reinforcement learning in Super Mario bros" by Akilesh.