Safe Reinforcement Learning with Dual Robustness
Reinforcement learning (RL) agents are vulnerable to adversarial disturbances, which can deteriorate task performance or break down safety specifications. Existing methods either address safety requirements under the assumption of no adversary (e.g., safe RL) or only focus on robustness against perf...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2024) vom: 15. Aug. |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Online verfügbar |
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