Author

Jiaming Zhang

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#machine learning Nov 2025

Exchange Policy Optimization Algorithm for Semi-Infinite Safe Reinforcement Learning

This paper proposes exchange policy optimization (EPO), an algorithmic framework that achieves optimal policy performance with provably bounded safety guarantees and derives an upper bound on the required number of iterations and quantifies the gap between the obtained policy and the true optimum.

Jiaming Zhang, Yujie Yang, Hao-Ning Wang et al. · arXiv.org · 1 citation