Balanced Domain Randomization for Safe Reinforcement Learning
Reinforcement Learning (RL) has enabled autonomous agents to achieve superhuman performance in diverse domains, including games, navigation, and robotic control. Despite these successes, RL agents often struggle with overfitting to specific training environments, which can hinder their adaptability...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-10-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/14/21/9710 |
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