ECNUdase · hccngu · May 22, 2020
diff --git a/.DS_Store b/.DS_Store
diff --git a/RL_introduction.pdf → 1. RL_introduction.pdf b/RL_introduction.pdf → 1. RL_introduction.pdf
diff --git a/2. Multi-Armed Bandits/.DS_Store b/2. Multi-Armed Bandits/.DS_Store
diff --git a/2. Multi-Armed Bandits/2. Multi-Armed Bandits.pdf b/2. Multi-Armed Bandits/2. Multi-Armed Bandits.pdf
diff --git a/2. Multi-Armed Bandits/参考文献/17_A Tutorial on Thompson Sampling.pdf b/2. Multi-Armed Bandits/参考文献/17_A Tutorial on Thompson Sampling.pdf
diff --git a/2. Multi-Armed Bandits/参考文献/Finite-time Analysis of the Multiarmed Bandit Problem.pdf b/2. Multi-Armed Bandits/参考文献/Finite-time Analysis of the Multiarmed Bandit Problem.pdf
diff --git a/2. Multi-Armed Bandits/参考文献/Introduction to Multi-Armed Bandits .pdf b/2. Multi-Armed Bandits/参考文献/Introduction to Multi-Armed Bandits .pdf
diff --git a/README.md b/README.md
@@ -4,4 +4,6 @@ slides and other materials
 | Title                                                        | Detail                                           | Author | link                                                         |
 | ------------------------------------------------------------ | ------------------------------------------------ | ------ | ------------------------------------------------------------ |
 | Introduction about RL | 强化学习简介，包含基本的要素、强化学习分类和一些例子 | 李娜  | [slide](https://github.com/ECNUdase/Reinforcement-Learning-2020/blob/master/RL_introduction.pdf) |
+| 第二章：多臂赌博机 | 多臂赌博机问题的各种经典解法，主要解决强化学习中的EE问题。 | 韩程程 | [slide](https://github.com/ECNUdase/Reinforcement-Learning-2020/blob/master/2. Multi-Armed Bandits/2. Multi-Armed Bandits.pdf) |
 | 第五章：蒙特卡洛方法 | 利用蒙特卡洛方法进行策略评估和策略改进，包含on-policy和off-policy下的不同做法 | 刘婷婷  | [slide](https://github.com/ECNUdase/Reinforcement-Learning-2020/blob/master/5.%20MC%20Learning.pdf) |
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