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eess.SY2026
Physics-informed Reinforcement Learning for Stochastic Reach-Avoid Analysis
Hikaru Hoshino, Yorie Nakahira
Stochastic reach-avoid analysis of controlled dynamical systems is an important tool for safety-critical control under uncertainty, in which the reach-avoid probability is characte…
eess.SY2025
Online Adaptive Probabilistic Safety Certificate with Language Guidance
Zhuoyuan Wang, Xiyu Deng, Hikaru Hoshino +1
Achieving long-term safety in uncertain/extreme environments while accounting for human preferences remains a fundamental challenge for autonomous systems. Existing methods often t…
eess.SY2024★ 4 cited
Physics-informed RL for Maximal Safety Probability Estimation
Hikaru Hoshino, Yorie Nakahira
Accurate risk quantification and reachability analysis are crucial for safe control and learning, but sampling from rare events, risky states, or long-term trajectories can be proh…