Hamilton-Jacobi Reachability in Reinforcement Learning: A Survey
Recent literature has proposed approaches that learn control policies with high performance while maintaining safety guarantees. Synthesizing Hamilton-Jacobi (HJ) reachable sets has become an effective tool for verifying safety and supervising the training of reinforcement learning-based control pol...
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| Main Authors: | Milan Ganai, Sicun Gao, Sylvia L. Herbert |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Open Journal of Control Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10645063/ |
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