pytorch-dqn

This is a simple implementation of the Deep Q-learning algorithm on the Atari Pong environment.

⚠ my implementation can't reach the best performance

## Requirements

• python >=3.4

• tensorboardX

• gym >= 0.10

• pytorch >= 0.4

Papers Related to the DQN

1. Playing Atari with Deep Reinforcement Learning [arxiv] [code]

2. Deep Reinforcement Learning with Double Q-learning [arxiv] [code]

3. Dueling Network Architectures for Deep Reinforcement Learning [arxiv] [code]

4. Prioritized Experience Replay [arxiv] [code]

5. Noisy Networks for Exploration [arxiv] [code]

6. A Distributional Perspective on Reinforcement Learning [arxiv] [code]

7. Rainbow: Combining Improvements in Deep Reinforcement Learning [arxiv] [code]

8. Distributional Reinforcement Learning with Quantile Regression [arxiv] [code]

9. Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation [arxiv] [code]

10. Neural Episodic Control [arxiv] [code]