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Atari 2600 games

The dataset used in this paper is a collection of state-action pairs generated by a pre-trained RL agent, used to train a self-supervised interpretable network (SSINet) to produce attention masks for explaining the agent's decisions.

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Cite this as

Wenjie Shi, Gao Huang, Shiji Song, Zhuoyuan Wang, Tingyu Lin, Cheng Wu (2024). Dataset: Atari 2600 games. https://doi.org/10.57702/z2n4g3e0

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Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2310.17173
Citation
  • https://doi.org/10.48550/arXiv.2003.07069
Author Wenjie Shi
More Authors
Gao Huang
Shiji Song
Zhuoyuan Wang
Tingyu Lin
Cheng Wu
Homepage https://github.com/shiwj16/SSINet