Sampling-Based Safe Reinforcement Learning.

arXiv:2605.19469v2 Announce Type: replace-cross Abstract: Safe exploration remains a fundamental challenge in reinforcement learning (RL), limiting the deployment of RL agents in the real world. We propose Sampling-Based Safe Reinforcement Learning (SBSRL), a