2 papers
cs.LG2026
Safe-RULE: Safe Reinforcement UnLEarning
Shixiong Jiang, Taozheng Zhu, Fanxin Kong
Offline safe reinforcement learning (Safe RL) enables policy learning without online interactions, making it suitable for safety-critical systems such as robotics systems. However,…
cs.LG2026
Vulnerability Analysis of Safe Reinforcement Learning via Inverse Constrained Reinforcement Learning
Jialiang Fan, Shixiong Jiang, Mengyu Liu +1
Safe reinforcement learning (Safe RL) aims to ensure policy performance while satisfying safety constraints. However, most existing Safe RL methods assume benign environments, maki…