为受控马尔可夫链量身定制的模型化自助法，理论证明与实证兼备，统计推断和强化学习研究者值得一读。
arXiv:2605.12410v2 Announce Type: replace-cross Abstract: We propose and analyze a model-based bootstrap for transition kernels in finite controlled M…
非参数化Koopman算子在控制领域的突破，为非线性系统建模与控制提供全新视角
arXiv:2405.07312v5 Announce Type: replace-cross Abstract: This paper presents a novel Koopman composition operator representation framework for contro…
用控制理论驯服多智能体LLM，为过程控制打造安全可审计的AI操作员。
arXiv:2606.30877v1 Announce Type: cross Abstract: Recent literature shows that large language models (LLMs) are useful for general-purpose tasks yet p…
从辛几何视角为有限时域庞特里亚金系统建立统一的灵敏度证书，获得时域一致的端点格林估计。
arXiv:2606.17762v1 Announce Type: cross Abstract: We study horizon-uniform local branches of finite-horizon discrete-time Pontryagin boundary value sy…
结合随机最优控制理论，为稀有事件分析提供新视角，交叉领域前沿方法值得关注。
arXiv:2604.13213v2 Announce Type: replace-cross Abstract: Rare events such as conformational changes in biomolecules, phase transitions, and chemical …
探讨控制问题中贝尔曼残差最小化的几何与收敛理论，为强化学习提供新视角
arXiv:2601.18840v4 Announce Type: replace Abstract: Markov decision problems are most commonly solved via dynamic programming. Another approach is Bel…