/memeagent

An unofficial implementation of MEME (Efficient Memory-based Exploration agent) from DeepMind

Primary LanguagePythonMIT LicenseMIT

MEME (Efficient Memory-based Exploration agent)

An unofficial implementation of MEME (Efficient Memory-based Exploration agent) from DeepMind

Learning Curves (Breakout)

drawing

TODO

  • Fix prioritized experience replay
  • Fix burnin functionality
  • Fix code for big burnin and rollout hyperparameter
  • Find bugs and test for correctness

Improvements

  • Bootstrapping with online network.
  • Target computation with tolerance.
  • Loss and priority normalization.
  • Cross-mixture training.
  • Normalizer-free torso network.
  • Shared torso with combined loss.
  • Robustifying behavior via policy distillation.

Agent57 Original Code

Readme Card

Citations

@article{kapturowski2022human,
  title={Human-level Atari 200x faster},
  author={Kapturowski, Steven and Campos, V{\'\i}ctor and Jiang, Ray and Raki{\'c}evi{\'c}, Nemanja and van Hasselt, Hado and Blundell, Charles and Badia, Adri{\`a} Puigdom{\`e}nech},
  journal={arXiv preprint arXiv:2209.07550},
  year={2022}
}