<p align="center">
<a href="https://www.youtube.com/watch?v=pieI7rOXELI&list=PLXO45tsB95cIplu-fLMpUEEZTwrDNh6Ba" target="_blank">
<img width="60%" src="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/blob/master/RL_cover.jpg" style="max-width:100%;">
</a>
</p>
<br>
# Reinforcement Learning Methods and Tutorials
In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.
**If you speak Chinese, visit [莫烦 Python](https://morvanzhou.github.io/tutorials/) or my [Youtube channel](https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg) for more.**
**As many requests about making these tutorials available in English, please find them in this playlist:** ([https://www.youtube.com/playlist?list=PLXO45tsB95cIplu-fLMpUEEZTwrDNh6Ba](https://www.youtube.com/playlist?list=PLXO45tsB95cIplu-fLMpUEEZTwrDNh6Ba))
# Table of Contents
* 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 (DQN)](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 (DDPG)](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 experiments](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments)
* [2D Car](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments/2D_car)
* [Robot arm](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments/Robot_arm)
* [BipedalWalker](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments/Solve_BipedalWalker)
* [LunarLander](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/experiments/Solve_LunarLander)
# Some RL Networks
### [Deep Q Network](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5_Deep_Q_Network)
<a href="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5_Deep_Q_Network">
<img class="course-image" src="https://morvanzhou.github.io/static/results/reinforcement-learning/4-3-2.png">
</a>
### [Double DQN](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.1_Double_DQN)
<a href="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.1_Double_DQN">
<img class="course-image" src="https://morvanzhou.github.io/static/results/reinforcement-learning/4-5-3.png">
</a>
### [Dueling DQN](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.3_Dueling_DQN)
<a href="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/5.3_Dueling_DQN">
<img class="course-image" src="https://morvanzhou.github.io/static/results/reinforcement-learning/4-7-4.png">
</a>
### [Actor Critic](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/8_Actor_Critic_Advantage)
<a href="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/8_Actor_Critic_Advantage">
<img class="course-image" src="https://morvanzhou.github.io/static/results/reinforcement-learning/6-1-1.png">
</a>
### [Deep Deterministic Policy Gradient](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/9_Deep_Deterministic_Policy_Gradient_DDPG)
<a href="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/9_Deep_Deterministic_Policy_Gradient_DDPG">
<img class="course-image" src="https://morvanzhou.github.io/static/results/reinforcement-learning/6-2-2.png">
</a>
### [A3C](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/10_A3C)
<a href="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/10_A3C">
<img class="course-image" src="https://morvanzhou.github.io/static/results/reinforcement-learning/6-3-2.png">
</a>
### [Proximal Policy Optimization (PPO)](https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/12_Proximal_Policy_Optimization)
<a href="https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow/tree/master/contents/12_Proximal_Policy_Optimization">
<img class="course-image" src="https://morvanzhou.github.io/static/results/reinforcement-learning/6-4-3.png">
</a>
# Donation
*If this does help you, please consider donating to support me for better tutorials. Any contribution is greatly appreciated!*
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莫烦python RL代码
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Reinforcement-learning-with-tensorflow-master.zip (58个子文件)
Reinforcement-learning-with-tensorflow-master
contents
5.2_Prioritized_Replay_DQN
RL_brain.py 12KB
run_MountainCar.py 2KB
7_Policy_gradient_softmax
RL_brain.py 4KB
run_MountainCar.py 2KB
run_CartPole.py 2KB
5_Deep_Q_Network
RL_brain.py 8KB
maze_env.py 4KB
DQN_modified.py 6KB
run_this.py 1KB
4_Sarsa_lambda_maze
RL_brain.py 3KB
maze_env.py 4KB
run_this.py 2KB
5.1_Double_DQN
RL_brain.py 7KB
run_Pendulum.py 2KB
3_Sarsa_maze
RL_brain.py 3KB
maze_env.py 4KB
run_this.py 1KB
12_Proximal_Policy_Optimization
discrete_DPPO.py 9KB
simply_PPO.py 6KB
DPPO.py 8KB
11_Dyna_Q
RL_brain.py 3KB
maze_env.py 4KB
run_this.py 1KB
8_Actor_Critic_Advantage
AC_continue_Pendulum.py 6KB
AC_CartPole.py 6KB
1_command_line_reinforcement_learning
treasure_on_right.py 3KB
2_Q_Learning_maze
RL_brain.py 2KB
maze_env.py 4KB
run_this.py 1KB
5.3_Dueling_DQN
RL_brain.py 7KB
run_Pendulum.py 2KB
10_A3C
A3C_continuous_action.py 8KB
A3C_RNN.py 9KB
A3C_distributed_tf.py 9KB
A3C_discrete_action.py 8KB
9_Deep_Deterministic_Policy_Gradient_DDPG
DDPG_update.py 6KB
DDPG.py 10KB
DDPG_update2.py 6KB
6_OpenAI_gym
RL_brain.py 8KB
run_MountainCar.py 1KB
run_CartPole.py 1KB
experiments
Solve_BipedalWalker
A3C.py 8KB
A3C_rnn.py 10KB
log
events.out.tfevents.1490801027.Morvan 1.07MB
DDPG.py 16KB
Solve_LunarLander
A3C.py 9KB
run_LunarLander.py 2KB
DuelingDQNPrioritizedReplay.py 13KB
2D_car
car_env.py 8KB
DDPG.py 10KB
collision.py 2KB
Robot_arm
A3C.py 8KB
arm_env.py 8KB
DDPG.py 10KB
DPPO.py 8KB
LICENCE 1KB
README.md 7KB
RL_cover.jpg 68KB
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