From ac05313a53cf50897f2460a3df3cf8dffe8e8e4f Mon Sep 17 00:00:00 2001 From: JohnJim0816 Date: Fri, 12 Mar 2021 16:55:05 +0800 Subject: [PATCH] update README --- docs/README.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/docs/README.md b/docs/README.md index 37b825a..90a1459 100644 --- a/docs/README.md +++ b/docs/README.md @@ -28,6 +28,22 @@ | [第十一章 模仿学习](https://datawhalechina.github.io/leedeeprl-notes/#/chapter11/chapter11) | [第十一章 习题](https://datawhalechina.github.io/leedeeprl-notes/#/chapter11/chapter11_questions&keywords) | | | [第十二章 深度确定性策略梯度 (DDPG) 算法](https://datawhalechina.github.io/leedeeprl-notes/#/chapter12/chapter12) | [第十二章 习题](https://datawhalechina.github.io/leedeeprl-notes/#/chapter12/chapter12_questions&keywords) | [项目三 使用 Policy-Based 方法实现 Pendulum-v0](https://datawhalechina.github.io/leedeeprl-notes/#/chapter12/project3) | | [第十三章 AlphaStar 论文解读](https://datawhalechina.github.io/leedeeprl-notes/#/chapter13/chapter13) ||| + +## 算法代码实现一览 + +| 算法名称 | 相关论文材料 | 备注 | 进度 | +| :----------------------: | :---------------------------------------------------------: | :--------------------------------: | :--: | +| On-Policy First-Visit MC | | 蒙特卡洛算法 | OK | +| Q-Learning | | | OK | +| SARSA | | | OK | +| DQN | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | | OK | +| DQN-cnn | [DQN-paper](https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf) | 与DQN相比使用了CNN而不是全链接网络 | OK | +| DoubleDQN | | | OK | +| Hierarchical DQN | [Hierarchical DQN](https://arxiv.org/abs/1604.06057) | | | +| PolicyGradient | | | OK | +| A2C | | | OK | +| DDPG | [DDPG Paper](https://arxiv.org/abs/1509.02971) | | OK | +| TD3 | [Twin Dueling DDPG Paper](https://arxiv.org/abs/1802.09477) | | | ## 贡献者