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New developments in stochastic maximum principle and relatedbackward stochastic differential equations

机译：随机最大原理和相关的倒向随机微分方程的新发展

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The author presents some developments in the stochastic maximumnprinciple of optimal control theory. Progress on backward stochasticndifferential equations that relates tightly to the stochastic maximumnprinciple is discussed. It is shown that theory continues to keep anclose relation to classical variational methods and Hamiltonian systemsnand its own special stochastic character. For this reason, the subjectnremains vigorous, not only by virtue of its important practicalnapplications, but also because it motivates other applied mathematicalnand practical problems

机译：作者介绍了最优控制理论的随机最大原理的一些发展。讨论了与随机极大值原理紧密相关的后向随机微分方程的进展。结果表明，理论继续与经典变分方法和哈密顿系统及其自身的特殊随机性保持密切联系。因此，该主题之所以保持活力，不仅是因为其重要的实际应用，而且还因为它激发了其他应用数学和实际问题。

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《1989 IEEE SOS/SOI technology conference》|1989年|p.2043-2047|共5页
会议地点 Stateline NV(US)
作者
Peng S.;
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作者单位

Dept. of Math., Shandong Univ.;

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会议组织
原文格式 PDF
正文语种 eng
中图分类半导体集成电路（固体电路）;
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1. A Mean-Field Stochastic Maximum Principle for Optimal Control of Forward-Backward Stochastic Differential Equations with Jumps via Malliavin Calculus [J] . Qing Zhou, Yong Ren Journal of Applied Mathematics and Physics . 2018,第1期

机译：通过Malliavin微积分跳跃最优控制的前向后向随机微分方程的均值随机最大原理
2. Pontryagin's Risk-Sensitive Stochastic Maximum Principle for Backward Stochastic Differential Equations with Application [J] . Chala Adel Bulletin of the Brazilian Mathematical Society . 2017,第3期

机译：Pontryagin具有应用的向后随机微分方程的风险敏感随机最大原理
3. Fully Coupled Mean-Field Forward-Backward Stochastic Differential Equations and Stochastic Maximum Principle [J] . HuiMin, YingPeng, YongliQin Abstract and applied analysis . 2014,第11期

机译：完全耦合平均场前后随机微分方程和随机最大原理
4. New developments in stochastic maximum principle and related backward stochastic differential equations [C] . Peng, S. . 1992

机译：随机最大值原理和相关的后向随机微分方程的新进展
5. Comparison principles for parabolic stochastic partial differential equations [D] . Li, Shiu-Tang. 2017

机译：抛物线随机偏微分方程的比较原理
6. Incorporating prior knowledge induced from stochastic differential equations in the classification of stochastic observations [O] . Amin Zollanvari, Edward R. Dougherty 2016

机译：将随机微分方程式衍生的先验知识纳入随机观测的分类中
7. A Mean-Field Stochastic Maximum Principle for Optimal Control of Forward-Backward Stochastic Differential Equations with Jumps via Malliavin Calculus [O] . Qing Zhou, Yong Ren 2018

机译：一种平均现场随机的最大最大原理，用于通过Malliavin Calmulus跳跃前向后随机微分方程的最佳控制

New developments in stochastic maximum principle and relatedbackward stochastic differential equations

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