A reinforcement learning framework for DouDizhu
DouZero
[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
DouZero is a reinforcement learning framework for DouDizhu (斗地主), the most popular card game in China. It is a shedding-type game where the player’s objective is to empty one’s hand of all cards before other players. DouDizhu is a very challenging domain with competition, collaboration, imperfect information, large state space, and particularly a massive set of possible actions where the legal actions vary significantly from turn to turn. DouZero is developed by AI Platform, Kwai Inc. (快手).
Cite this Work
For now, please cite our Arxiv version:
Zha, Daochen, et al. “DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning.” arXiv preprint arXiv:2106.06135 (2021).
@article{zha2021douzero,
title={DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning},
author={Zha, Daochen