Physics-informed RL for Maximal Safety Probability Estimation
Author:
Affiliation:
1. University of Hyoto,Department of Electrical Materials and Engineering,Hyogo,Japan,671–2280
2. Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,PA,USA,15213
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10644130/10644150/10644621.pdf?arnumber=10644621
Reference27 articles.
1. A Risk-Sensitive Finite-Time Reachability Approach for Safety of Stochastic Dynamic Systems
2. Myopically Verifiable Probabilistic Certificate for Long-term Safety
3. Safe exploration in reinforcement learning: Theory and applications in robotics;Berkenkamp,2019
4. Safe Learning and Optimization Techniques: Towards a Survey of the State of the Art
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