A STOCHASTIC MAXIMUM PRINCIPLE FOR GENERAL MEAN-FIELD BACKWARD DOUBLY STOCHASTIC CONTROL

In this paper we study the optimal control problems of general Mckean-Vlasov for backward doubly stochastic differential equations (BDSDEs), in which the coefficients depend on the state of the solution process as well as of its law. We establish a stochastic maximum principle on the hypothesis that...

Full description

Saved in:
Bibliographic Details
Published inTWMS journal of applied and engineering mathematics Vol. 14; no. 1; p. 353
Main Authors Aoun, S, Tamer, L
Format Journal Article
LanguageEnglish
Published Istanbul Turkic World Mathematical Society 01.01.2024
Elman Hasanoglu
Subjects
Differential equations
Euclidean space
Maximum principle
Optimal control
Partial differential equations
Random variables
Stochastic processes
Online AccessGet full text

Cover

More Information
Summary:In this paper we study the optimal control problems of general Mckean-Vlasov for backward doubly stochastic differential equations (BDSDEs), in which the coefficients depend on the state of the solution process as well as of its law. We establish a stochastic maximum principle on the hypothesis that the control field is convex. For example, an example of a control problem is offered and solved using the primary result. Keywords: Backward doubly stochastic differential equations. Optimal control. McKean-Vlasov differential equations. Probability measure. Derivative with respect to measure. AMS Subject Classification: 93E20, 60H10.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2146-1147
2146-1147