# deep-RL-elements

**Repository Path**: beamiter/deep-RL-elements

## Basic Information

- **Project Name**: deep-RL-elements
- **Description**: Deep RL algorithm in pytorch
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-01-27
- **Last Updated**: 2021-08-30

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Deep RL elements
Deep RL algorithm with pytorch (written in jupyter notebook). Algorithms are tested on Atari Games, mostly with Pong. Feel free to ask questions and report bugs with Issues. :)
### 1. Deep Q-learning
### 2. DQN with prioritized experience replay (PER)
### 3. Double DQN (DDQN)
### 4. Dueling DQN
### 5. DQN with soft update (Soft DQN)
### 6. DQN with noisy net (Noisy DQN)
### 7. DQN with intrinsic curiosity module (ICM DQN)
### 8. Deep recurrent Q-learning (DRQN)
### 9. N-step DQN

# Prerequisite 
- torch 1.4.0
- gym[atari]
- tensorboardX 

# Other useful deep RL algorithm zoos (pytorch)
- [Reinforcement-Learning](https://github.com/andri27-ts/Reinforcement-Learning)
- [DeepRL-Tutorials](https://github.com/qfettes/DeepRL-Tutorials)
- [Deep-Reinforcement-Learning-Algorithms-with-PyTorch](https://github.com/p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch)