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Exchange Policy Optimization Algorithm for Semi-Infinite Safe Reinforcement Learning

Zhang, Jiaming et al.
arXiv (All) · Papers
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Safe reinforcement learning (RL) aims to optimize long-term performance while adhering to safety requirements. However, many practical applications involve an infinite number of constraints, forming semi-infinite safe RL (SI-safe RL). Such scenarios typically appear when safety conditions must be en
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