English(EN) Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence

随机控制问题的新型连续策略-值迭代算法

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-15 04:00

已开发出一种用于随机控制问题的新型连续策略-值迭代算法，旨在同时更新值函数并识别最优控制。该方法利用了 Langevin 型动力学，可应用于具有无限视界的熵正则化和经典控制问题。在 Hamiltonian 单调性条件下，该算法可收敛到最优控制，从而能够利用机器学习中的分布采样和非凸学习技术。 AI

影响这项研究可能会推进适用于强化学习和其他涉及顺序决策的 AI 领域的优化技术。

排序理由该集群包含一篇详细介绍随机控制问题新算法的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Qi Feng, Gu Wang · 2026-07-15 04:00

随机控制问题的连续策略和价值迭代及其收敛性

arXiv:2506.08121v2 Announce Type: replace-cross Abstract: We introduce a continuous policy-value iteration algorithm where the approximations of the value function of a stochastic control problem and the optimal control are simultaneously updated through Langevin-type dynamics. T…