update readme and add code distribution
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qiwang067
@@ -66,21 +66,21 @@ PDF版本是全书初稿，人民邮电出版社的编辑老师们对初稿进
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## 内容导航
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| 章节 | 习题 | 相关项目 |
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| ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
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| [第一章 强化学习基础](https://datawhalechina.github.io/easy-rl/#/chapter1/chapter1) | [第一章 习题](https://datawhalechina.github.io/easy-rl/#/chapter1/chapter1_questions&keywords) | |
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| [第二章 马尔可夫决策过程 (MDP)](https://datawhalechina.github.io/easy-rl/#/chapter2/chapter2) | [第二章 习题](https://datawhalechina.github.io/easy-rl/#/chapter2/chapter2_questions&keywords) | |
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| [第三章 表格型方法](https://datawhalechina.github.io/easy-rl/#/chapter3/chapter3) | [第三章 习题](https://datawhalechina.github.io/easy-rl/#/chapter3/chapter3_questions&keywords) | [Q-learning算法实战](https://datawhalechina.github.io/easy-rl/#/chapter3/project1) |
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| [第四章 策略梯度](https://datawhalechina.github.io/easy-rl/#/chapter4/chapter4) | [第四章 习题](https://datawhalechina.github.io/easy-rl/#/chapter4/chapter4_questions&keywords) | |
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| [第五章 近端策略优化 (PPO) 算法](https://datawhalechina.github.io/easy-rl/#/chapter5/chapter5) | [第五章 习题](https://datawhalechina.github.io/easy-rl/#/chapter5/chapter5_questions&keywords) | |
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| [第六章 DQN (基本概念)](https://datawhalechina.github.io/easy-rl/#/chapter6/chapter6) | [第六章 习题](https://datawhalechina.github.io/easy-rl/#/chapter6/chapter6_questions&keywords) | |
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| [第七章 DQN (进阶技巧)](https://datawhalechina.github.io/easy-rl/#/chapter7/chapter7) | [第七章 习题](https://datawhalechina.github.io/easy-rl/#/chapter7/chapter7_questions&keywords) | [DQN算法实战](https://datawhalechina.github.io/easy-rl/#/chapter7/project2) |
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| [第八章 DQN (连续动作)](https://datawhalechina.github.io/easy-rl/#/chapter8/chapter8) | [第八章 习题](https://datawhalechina.github.io/easy-rl/#/chapter8/chapter8_questions&keywords) | |
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| [第九章 演员-评论员算法](https://datawhalechina.github.io/easy-rl/#/chapter9/chapter9) | [第九章 习题](https://datawhalechina.github.io/easy-rl/#/chapter9/chapter9_questions&keywords) | |
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| [第十章 稀疏奖励](https://datawhalechina.github.io/easy-rl/#/chapter10/chapter10) | [第十章 习题](https://datawhalechina.github.io/easy-rl/#/chapter10/chapter10_questions&keywords) | |
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| [第十一章 模仿学习](https://datawhalechina.github.io/easy-rl/#/chapter11/chapter11) | [第十一章 习题](https://datawhalechina.github.io/easy-rl/#/chapter11/chapter11_questions&keywords) | |
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| [第十二章 深度确定性策略梯度 (DDPG) 算法](https://datawhalechina.github.io/easy-rl/#/chapter12/chapter12) | [第十二章 习题](https://datawhalechina.github.io/easy-rl/#/chapter12/chapter12_questions&keywords) | [DDPG算法实战](https://datawhalechina.github.io/easy-rl/#/chapter12/project3) |
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| [第十三章 AlphaStar 论文解读](https://datawhalechina.github.io/easy-rl/#/chapter13/chapter13) | | |
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| 章节 | 习题 | 相关项目 | 配套代码 |
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| ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
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| [第一章 强化学习基础](https://datawhalechina.github.io/easy-rl/#/chapter1/chapter1) | [第一章 习题](https://datawhalechina.github.io/easy-rl/#/chapter1/chapter1_questions&keywords) | | |
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| [第二章 马尔可夫决策过程 (MDP)](https://datawhalechina.github.io/easy-rl/#/chapter2/chapter2) | [第二章 习题](https://datawhalechina.github.io/easy-rl/#/chapter2/chapter2_questions&keywords) | | [值迭代算法](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/Value%20Iteration/value_iteration.ipynb) |
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| [第三章 表格型方法](https://datawhalechina.github.io/easy-rl/#/chapter3/chapter3) | [第三章 习题](https://datawhalechina.github.io/easy-rl/#/chapter3/chapter3_questions&keywords) | [Q-learning算法实战](https://datawhalechina.github.io/easy-rl/#/chapter3/project1) | [Q-learning](https://github.com/datawhalechina/easy-rl/tree/master/notebooks/Q-learning)，[Sarsa](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/Sarsa.ipynb)，[蒙特卡洛](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/MonteCarlo.ipynb) |
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| [第四章 策略梯度](https://datawhalechina.github.io/easy-rl/#/chapter4/chapter4) | [第四章 习题](https://datawhalechina.github.io/easy-rl/#/chapter4/chapter4_questions&keywords) | | [策略梯度](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/PolicyGradient.ipynb) |
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| [第五章 近端策略优化 (PPO) 算法](https://datawhalechina.github.io/easy-rl/#/chapter5/chapter5) | [第五章 习题](https://datawhalechina.github.io/easy-rl/#/chapter5/chapter5_questions&keywords) | | [PPO](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/PPO.ipynb) |
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| [第六章 DQN (基本概念)](https://datawhalechina.github.io/easy-rl/#/chapter6/chapter6) | [第六章 习题](https://datawhalechina.github.io/easy-rl/#/chapter6/chapter6_questions&keywords) | | [DQN](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/DQN.ipynb) |
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| [第七章 DQN (进阶技巧)](https://datawhalechina.github.io/easy-rl/#/chapter7/chapter7) | [第七章 习题](https://datawhalechina.github.io/easy-rl/#/chapter7/chapter7_questions&keywords) | [DQN算法实战](https://datawhalechina.github.io/easy-rl/#/chapter7/project2) | [Double DQN](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/DoubleDQN.ipynb)，[Dueling DQN](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/DuelingDQN.ipynb)，[PER DQN](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/PER_DQN.ipynb)，[Noisy DQN](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/NoisyDQN.ipynb) |
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| [第八章 DQN (连续动作)](https://datawhalechina.github.io/easy-rl/#/chapter8/chapter8) | [第八章 习题](https://datawhalechina.github.io/easy-rl/#/chapter8/chapter8_questions&keywords) | | |
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| [第九章 演员-评论员算法](https://datawhalechina.github.io/easy-rl/#/chapter9/chapter9) | [第九章 习题](https://datawhalechina.github.io/easy-rl/#/chapter9/chapter9_questions&keywords) | | [A2C](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/A2C.ipynb) |
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| [第十章 稀疏奖励](https://datawhalechina.github.io/easy-rl/#/chapter10/chapter10) | [第十章 习题](https://datawhalechina.github.io/easy-rl/#/chapter10/chapter10_questions&keywords) | | |
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| [第十一章 模仿学习](https://datawhalechina.github.io/easy-rl/#/chapter11/chapter11) | [第十一章 习题](https://datawhalechina.github.io/easy-rl/#/chapter11/chapter11_questions&keywords) | | |
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| [第十二章 深度确定性策略梯度 (DDPG) 算法](https://datawhalechina.github.io/easy-rl/#/chapter12/chapter12) | [第十二章 习题](https://datawhalechina.github.io/easy-rl/#/chapter12/chapter12_questions&keywords) | [DDPG算法实战](https://datawhalechina.github.io/easy-rl/#/chapter12/project3) | [DDPG](https://github.com/datawhalechina/easy-rl/blob/master/notebooks/DDPG.ipynb) |
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| [第十三章 AlphaStar 论文解读](https://datawhalechina.github.io/easy-rl/#/chapter13/chapter13) | | | |
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## 算法实战
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算法实战部分包括附书代码和JoyRL代码：
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