Self-Imitation Learning

Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee
6/14/2018
cs.LGcs.AIstat.ML

Official code: junhyukoh/self-imitation-learning (279 stars, MIT, last commit 2020-04-18).

Abstract

This paper proposes Self-Imitation Learning (SIL), a simple off-policy actor-critic algorithm that learns to reproduce the agent's past good decisions. This algorithm is designed to verify our hypothesis that exploiting past good experiences can indirectly drive deep exploration. Our empirical results show that SIL significantly improves advantage actor-critic (A2C) on several hard exploration Atari games and is competitive to the state-of-the-art count-based exploration methods. We also show that SIL improves proximal policy optimization (PPO) on MuJoCo tasks.

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Code Implementations(1)

MIT

ICML 2018 Self-Imitation Learning

27943Python, DockerfileMay 25, 20186 years agoMIT

Cite this paper

@article{oh2018selfimitation,
  title  = {Self-Imitation Learning},
  author = {Junhyuk Oh and Yijie Guo and Satinder Singh and Honglak Lee},
  year   = {2018},
  eprint = {1806.05635},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1806.05635}
}

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