MorvanZhou/Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials
| repo name | MorvanZhou/Reinforcement-learning-with-tensorflow |
| repo link | https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow |
| homepage | https://morvanzhou.github.io/tutorials/machine-learning/reinforcement-learning/ |
| language | Python |
| size (curr.) | 431 kB |
| stars (curr.) | 4883 |
| created | 2017-05-06 |
| license | MIT License |
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 or my Youtube channel 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)
Table of Contents
- Tutorials
- Simple entry example
- Q-learning
- Sarsa
- Sarsa(lambda)
- Deep Q Network (DQN)
- Using OpenAI Gym
- Double DQN
- DQN with Prioitized Experience Replay
- Dueling DQN
- Policy Gradients
- Actor-Critic
- Deep Deterministic Policy Gradient (DDPG)
- A3C
- Dyna-Q
- Proximal Policy Optimization (PPO)
- Curiosity Model, Random Network Distillation (RND)
- Some of my experiments
Some RL Networks
Deep Q Network
Double DQN
Dueling DQN
Actor Critic
Deep Deterministic Policy Gradient
A3C
Proximal Policy Optimization (PPO)
Curiosity Model
Donation
If this does help you, please consider donating to support me for better tutorials. Any contribution is greatly appreciated!
