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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Bibliographic Details
Main Authors: Milan Ganai, Sicun Gao, Sylvia L. Herbert
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of Control Systems
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10645063/
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