update

Author: MorvanZhou

README.md

@@ -18,23 +18,23 @@ In these tutorials for reinforcement learning, it covers from the basic RL algor
 
 # Table of Contents
 
-* [Simple entry example](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/1_command_line_reinforcement_learning)
-* [Q-learning](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/2_Q_Learning_maze)
-* [Sarsa](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/3_Sarsa_maze)
-* [Sarsa(lambda)](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/4_Sarsa_lambda_maze)
-* [Deep Q Network](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5_Deep_Q_Network)
-* [Using OpenAI Gym](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/6_OpenAI_gym)
-* [Double DQN](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.1_Double_DQN)
-* [DQN with Prioitized Experience Replay](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.2_Prioritized_Replay_DQN)
-* [Dueling DQN](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.3_Dueling_DQN)
-* [Policy Gradients](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/7_Policy_gradient_softmax)
-* [Actor Critic](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/8_Actor_Critic_Advantage)
-* [Deep Deterministic Policy Gradient](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/9_Deep_Deterministic_Policy_Gradient_DDPG)
-* [A3C](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/10_A3C)
-* [Dyna-Q](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/11_Dyna_Q)
-* [Proximal Policy Optimization (PPO)](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/12_Proximal_Policy_Optimization)
-
-### [Some of my experients](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments)
+* Tutorials
+    * [Simple entry example](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/1_command_line_reinforcement_learning)
+    * [Q-learning](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/2_Q_Learning_maze)
+    * [Sarsa](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/3_Sarsa_maze)
+    * [Sarsa(lambda)](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/4_Sarsa_lambda_maze)
+    * [Deep Q Network](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5_Deep_Q_Network)
+    * [Using OpenAI Gym](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/6_OpenAI_gym)
+    * [Double DQN](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.1_Double_DQN)
+    * [DQN with Prioitized Experience Replay](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.2_Prioritized_Replay_DQN)
+    * [Dueling DQN](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.3_Dueling_DQN)
+    * [Policy Gradients](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/7_Policy_gradient_softmax)
+    * [Actor Critic](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/8_Actor_Critic_Advantage)
+    * [Deep Deterministic Policy Gradient](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/9_Deep_Deterministic_Policy_Gradient_DDPG)
+    * [A3C](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/10_A3C)
+    * [Dyna-Q](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/11_Dyna_Q)
+    * [Proximal Policy Optimization (PPO)](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/12_Proximal_Policy_Optimization)
+* [Some of my experients](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments)
 
 # Donation