Self-Supervised Discovering of Interpretable Features for Reinforcement Learning
Deep reinforcement learning (RL) has recently led to many breakthroughs on a range of complex control tasks. However, the agent's decision-making process is generally not transparent. The lack of interpretability hinders the applicability of RL in safety-critical scenarios. While several method...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 5 vom: 13. Mai, Seite 2712-2724
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| 1. Verfasser: |
Shi, Wenjie
(VerfasserIn) |
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| Weitere Verfasser: |
Huang, Gao,
Song, Shiji,
Wang, Zhuoyuan,
Lin, Tingyu,
Wu, Cheng |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
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