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cs.LG2026
Extreme Value Policy Optimization for Safe Reinforcement Learning
Shiqing Gao, Yihang Zhou, Shuai Shao +5
Ensuring safety is a critical challenge in applying Reinforcement Learning (RL) to real-world scenarios. Constrained Reinforcement Learning (CRL) addresses this by maximizing retur…
cs.LG2026
Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
Shiqing Gao, Jiaxin Ding, Luoyi Fu +1
Constrained Reinforcement Learning (CRL) aims to maximize cumulative rewards while satisfying constraints. However, existing CRL algorithms often encounter significant constraint v…