jiseongHAN / Super-Mario-RL

🍄Reinforcement Learning: Super Mario Bros with dueling dqn🍄

🍄 Super-Mario-RL

This is a private project to make Super Mario Agent.

It consists of training an agent to clear Super Mario Bros with deep reinforcement learning methods.

Here are my super mario agents with dueling network. ( trained 7,000 epoch )

Get started

Cloning git

git clone https://github.com/jiseongHAN/Super-Mario-RL.git
cd Super-Mario-RL

Install Requirements

pip install -r requirements.txt

Or Install Manually

• Install openAI gym

pip install 'gym'

• Install Pytorch

pip install torch torchvision

• Install nes-py

pip install nes-py

• Install gym-super-mario-bros

pip install gym-super-mario-bros

Running

Train

• Train with dueling dqn.

python duel_dqn.py

Result

• score.p : save total score every 50 episode
• *.pth : save weight of q, q_target every 50 training

Evaluate

• (Now, pre-trained agent has been corrupted😢)
• Test and render trained agent.
• To test our agent, we need 'q_target.pth' that generated at the training step.

python eval.py

• Or you can use your own agent.

python eval.py your_own_agent.pth

Reference

Wang, Ziyu, et al. "Dueling network architectures for deep reinforcement learning." International conference on machine learning. PMLR, 2016.