Maximum principle for optimal control of interacting particle system: stochastic flow model

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Dorogovtsev, Andrey A., Han, Yuecai, Hlyniana, Kateryna, Li, Yuhang
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916733444423680
author Dorogovtsev, Andrey A.
Han, Yuecai
Hlyniana, Kateryna
Li, Yuhang
author_facet Dorogovtsev, Andrey A.
Han, Yuecai
Hlyniana, Kateryna
Li, Yuhang
contents In this paper, we consider the stochastic optimal control problem for the interacting particle system. We obtain the stochastic maximum principle of the optimal control system by introducing a generalized backward stochastic differential equation with interaction. The existence and uniqueness of the solution of this type of equation is proved. We derive the necessary condition that the optimal control should satisfy. As an application, the linear quadratic case is investigated to illustrate the main results.
format Preprint
id arxiv_https___arxiv_org_abs_2401_08075
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Maximum principle for optimal control of interacting particle system: stochastic flow model
Dorogovtsev, Andrey A.
Han, Yuecai
Hlyniana, Kateryna
Li, Yuhang
Probability
In this paper, we consider the stochastic optimal control problem for the interacting particle system. We obtain the stochastic maximum principle of the optimal control system by introducing a generalized backward stochastic differential equation with interaction. The existence and uniqueness of the solution of this type of equation is proved. We derive the necessary condition that the optimal control should satisfy. As an application, the linear quadratic case is investigated to illustrate the main results.
title Maximum principle for optimal control of interacting particle system: stochastic flow model
topic Probability
url https://arxiv.org/abs/2401.08075