Stochastic maximum principle for partially observed risk-sensitive optimal control problems of mean-field forward-backward stochastic differential equations

Ma Heping; Wang Weifeng

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Stochastic maximum principle for partially observed risk-sensitive optimal control problems of mean-field forward-backward stochastic differential equations

机译：Stochastic maximum principle for partially observed risk-sensitive optimal control problems of mean-field forward-backward stochastic differential equations

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摘要

This paper deals with a partially observed risk-sensitive optimal control problem described by mean-field forward-backward stochastic differential equations and the cost functional is a mean-field exponential of integral type. By using Girsanov's theorem as well as classical convex variational techniques, we obtain two risk-sensitive maximum principles, which are characterized in terms of the variational inequalities. Moreover, under certain concavity assumption, we give the sufficient condition for the optimality. Through the application of results, we consider the linear-quadratic risk-sensitive optimal control problem under partially observed information and fully observed information, respectively.

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来源
《Optimal Control Applications and Methods》 |2022年第2期|532-552|共21页
作者
Ma Heping; Wang Weifeng;
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作者单位

Hubei Univ Technol;

South Cent Univ Nationalities;

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原文格式 PDF
正文语种英语
中图分类应用数学;
关键词
convex variational techniques; Girsanov's theorem; partial information; risk-sensitive optimal control; stochastic maximum principle; CONTROL SYSTEMS; LIMIT;

Stochastic maximum principle for partially observed risk-sensitive optimal control problems of mean-field forward-backward stochastic differential equations

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