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}
}