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|[第九章 演员-评论员算法](https://datawhalechina.github.io/leedeeprl-notes/#/chapter9/chapter9) | [第九章习题](https://datawhalechina.github.io/leedeeprl-notes/#/chapter9/chapter9_questions&keywords) | |
|[第十章 稀疏奖励](https://datawhalechina.github.io/leedeeprl-notes/#/chapter10/chapter10) | [第十章习题](https://datawhalechina.github.io/leedeeprl-notes/#/chapter10/chapter10_questions&keywords) | |
|[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) | | [项目三 使用 Policy-Based 方法实现 Pendulum-v0](https://datawhalechina.github.io/leedeeprl-notes/#/chapter12/project3) |
|[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) |
## 主要贡献者
| 作者 | 贡献 |