Rainbow: Combining Improvements in Deep Reinforcement Learning
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Use numpy arrays for speed
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README.md

Rainbow

MIT License

Rainbow: Combining Improvements in Deep Reinforcement Learning [1].

Results and pretrained models can be found in the releases.

  • DQN [2]
  • Double DQN [3]
  • Prioritised Experience Replay [4]
  • Dueling Network Architecture [5]
  • Multi-step Returns [6]
  • Distributional RL [7]
  • Noisy Nets [8]

Requirements

To install all dependencies with Anaconda run conda env create -f environment.yml and use source activate rainbow to activate the environment.

Available Atari games can be found in the atari-py ROMs folder.

Acknowledgements

References

[1] Rainbow: Combining Improvements in Deep Reinforcement Learning
[2] Playing Atari with Deep Reinforcement Learning
[3] Deep Reinforcement Learning with Double Q-learning
[4] Prioritized Experience Replay
[5] Dueling Network Architectures for Deep Reinforcement Learning
[6] Reinforcement Learning: An Introduction
[7] A Distributional Perspective on Reinforcement Learning
[8] Noisy Networks for Exploration