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arXiv 2404.06960math.PR
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由占据测度控制的布朗粒子

Brownian particles controlled by their occupation measure

Loïc Béthencourt, Rémi Catellier, Etienne Tanré

AI总结:

本文针对布朗粒子的有限时间水平线性二次随机控制问题,推导占据测度流的Itô公式以得到Hamilton-Jacobi-Bellman方程,借助Feynman-Kac公式和Boué-Dupuis公式构造最优策略与轨迹,并在代价函数为粒子香肠体积时验证结果。

摘要:

本文研究布朗粒子的有限时间水平线性二次随机控制问题,其中代价函数依赖于粒子的状态和占据测度。为解决该问题,我们推导了占据测度流的Itô公式,这使我们能够得到相关的Hamilton-Jacobi-Bellman方程。然后,借助Feynman-Kac公式和Boué-Dupuis公式,我们构造了最优策略和最优轨迹。最后,当代价函数为粒子相关香肠的体积时,我们展示了研究结果。

英文摘要:

In this article, we study a finite horizon linear-quadratic stochastic control problem for Brownian particles, where the cost functions depend on the state and the occupation measure of the particles. To address this problem, we develop an Itô formula for the flow of occupation measure, which enables us to derive the associated Hamilton-Jacobi-Bellman equation. Then, thanks to a Feynman-Kac formula and the Boué-Dupuis formula, we construct an optimal strategy and an optimal trajectory. Finally, we illustrate our result when the cost-function is the volume of the sausage associated to the particles.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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