# DRL

**Repository Path**: wolf953/DRL

## Basic Information

- **Project Name**: DRL
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2021-01-26
- **Last Updated**: 2022-03-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Deep Reinforcement Learning




1. **Overview.**


    * Reinforcement Learning 
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/1_Basics_1.pdf)] 
    [[lecture note](https://github.com/wangshusen/DeepLearning/blob/master/LectureNotes/DRL/DRL.pdf)] 
    [[Video (in Chinese)](https://youtu.be/vmkRMvhCW5c)].

    * Value-Based Learning 
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/1_Basics_2.pdf)] 
    [[Video (in Chinese)](https://youtu.be/jflq6vNcZyA)].

    * Policy-Based Learning 
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/1_Basics_3.pdf)] 
    [[Video (in Chinese)](https://youtu.be/qI0vyfR2_Rc)].

    * Actor-Critic Methods 
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/1_Basics_4.pdf)] 
    [[Video (in Chinese)](https://youtu.be/xjd7Jq9wPQY)].

    * AlphaGo 
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/1_Basics_5.pdf)] 
    [[Video (in Chinese)](https://youtu.be/zHojAp5vkRE)].
    
    



2. **TD Learning.**
    
    * Sarsa
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/2_TD_1.pdf)] 
    [[Video (in Chinese)](https://youtu.be/-cYWdUubB6Q)].
    
    * Q-learning
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/2_TD_2.pdf)] 
    [[Video (in Chinese)](https://youtu.be/Ymy2w3DGn2U)].
    
    * Multi-Step TD Target
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/2_TD_3.pdf)] 
    [[Video (in Chinese)](https://youtu.be/UqTP138IATc)].
    
    
    


3. **Advanced Topics on Value-Based Learning.**


    * Experience Replay (ER) & Prioritized ER
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/3_DQN_1.pdf)]
    [[Video (in Chinese)](https://youtu.be/rhslMPmj7SY)].
    
    * Overestimation, Target Network, & Double DQN
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/3_DQN_2.pdf)] 
    [[Video (in Chinese)](https://youtu.be/X2-56QN79zc)].
    
    * Dueling Networks
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/3_DQN_3.pdf)]
    [[Video (in Chinese)](https://youtu.be/DBux6cA0EoM)].




4. **Policy Gradient with Baseline.**


    * Policy Gradient with Baseline
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/4_Policy_1.pdf)]
    [[Video (in Chinese)](https://youtu.be/yNEqbptitZs)].
    
    * REINFORCE with Baseline
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/4_Policy_2.pdf)]
    [[Video (in Chinese)](https://youtu.be/Ob78ADXTQNo)].
    
    * Advantage Actor-Critic (A2C)
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/4_Policy_3.pdf)]
    [[Video (in Chinese)](https://youtu.be/mtT4TSGSon8)].
    
    * REINFORCE versus A2C
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/4_Policy_4.pdf)]
    [[Video (in Chinese)](https://youtu.be/hN9WMIMMeAI)].
    


5. **Advanced Topics on Policy-Based Learning.**
    
    * Trust-Region Policy Optimization (TRPO).
    
    * Policy Network + RNNs.



6. **Dealing with Continuous Action Space.**


    * Discrete versus Continuous Control.
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/6_Continuous_1.pdf)] 

    * Deterministic Policy Gradient (DPG) for Continuous Control.
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/6_Continuous_2.pdf)] 

    * Stochastic Policy Gradient for Continuous Control.
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/6_Continuous_3.pdf)] 
    
    

7. **Multi-Agent Reinforcement Learning.**


    * Basics and Challenges 
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/7_MARL_1.pdf)] 
    [[Video (in Chinese)](https://youtu.be/KN-XMQFTD0o)].

    * Centralized VS Decentralized 
    [[slides](https://github.com/wangshusen/DRL/blob/master/Slides/7_MARL_2.pdf)] 
    [[Video (in Chinese)](https://youtu.be/0HV1hsjd1y8)].



8. **Imitation Learning.**


    * Inverse Reinforcement Learning.
    
    * Generative Adversarial Imitation Learning (GAIL).