This is an official tutorial for RLCard: A Toolkit for Reinforcement Learning in Card Games. We provide step-by-step instructions and running examples with Jupyter Notebook in Python3. The tutorial is available in Colab, where you can try your experiments in the cloud interactively.

• Official Website: http://www.rlcard.org
• Paper: https://arxiv.org/abs/1910.04376
• Resources: Awesome-Game-AI

• Playing with Random Agents
• Training DQN on Blackjack
• Training CFR on Leduc Hold'em
• Having Fun with Pretrained Leduc Model
• Training DMC on Dou Dizhu

• Playing with Random Agents
• Training DQN on Blackjack
• Training CFR on Leduc Hold'em
• Having Fun with Pretrained Leduc Model
• Training DMC on Dou Dizhu

Contribution to this project is greatly appreciated! Please create an issue/pull request for feedbacks or more tutorials.

If you find this repo useful, you may cite:

Zha, Daochen, et al. "RLCard: A Platform for Reinforcement Learning in Card Games." IJCAI. 2020.

@inproceedings{zha2020rlcard,
  title={RLCard: A Platform for Reinforcement Learning in Card Games},
  author={Zha, Daochen and Lai, Kwei-Herng and Huang, Songyi and Cao, Yuanpu and Reddy, Keerthana and Vargas, Juan and Nguyen, Alex and Wei, Ruzhe and Guo, Junyu and Hu, Xia},
  booktitle={IJCAI},
  year={2020}
}