On partially observed optimal singular control of McKean–Vlasov stochastic systems: Maximum principle approach
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Date
2022
Authors
Nour El Houda Abada
Mokhtar Hafayed
Shahlar Meherrem
Journal Title
Journal ISSN
Volume Title
Publisher
John Wiley and Sons Ltd
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
In this paper we study partially observed optimal stochastic singular control problems of general Mckean–Vlasov type with correlated noises between the system and the observation. The control variable has two components the first being absolutely continuous and the second is a bounded variation nondecreasing continuous on the right with left limits. The dynamic system is governed by Itô-type controlled stochastic differential equation. The coefficients of the dynamic depend on the state process and of its probability law and the continuous control variable. In terms of a classical convex variational techniques we establish a set of necessary conditions of optimal singular control in the form of maximum principle. Our main result is proved by applying Girsanov's theorem and the derivatives with respect to probability law in Lions' sense. To illustrate our theoretical result we study partially observed linear-quadratic singular control problem of McKean–Vlasov type. © 2022 Elsevier B.V. All rights reserved.
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ORCID
Keywords
Derivatives With Respect To Probability Measure, Girsanov's Theorem, Mckean–vlasov Stochastic System With Correlated Noises, Nonlinear Filtering, Partially Observed Optimal Singular Control, Stochastic Singular Control, Maximum Principle, Nonlinear Filtering, Probability, Stochastic Control Systems, Variational Techniques, White Noise, Control Problems, Control Variable, Correlated Noise, Derivative With Respect To Probability Measure, Girsanov Theorems, Mckean–vlasov Stochastic System With Correlated Noise, Optimal Singular Controls, Partially Observed Optimal Singular Control, Probability Measures, Stochastic Singular Control, Stochastic Systems, Maximum principle, Nonlinear filtering, Probability, Stochastic control systems, Variational techniques, White noise, Control problems, Control variable, Correlated noise, Derivative with respect to probability measure, Girsanov theorems, Mckean–vlasov stochastic system with correlated noise, Optimal singular controls, Partially observed optimal singular control, Probability measures, Stochastic singular control, Stochastic systems, Girsanov’s Theorem, Derivatives with Respect to Probability Measure, McKean–Vlasov Stochastic System with Correlated Noises, McKean-Vlasov Stochastic System with Correlated Noises, Nonlinear Filtering, Partially Observed Optimal Singular Control, Stochastic Singular Control, derivatives with respect to probability measure, Girsanov's theorem, nonlinear filtering, partially observed optimal singular control, stochastic singular control, Optimal stochastic control, McKean-Vlasov stochastic system with correlated noises, Stochastic ordinary differential equations (aspects of stochastic analysis)
Fields of Science
0209 industrial biotechnology, 02 engineering and technology
Citation
WoS Q
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OpenCitations Citation Count
6
Source
Mathematical Methods in the Applied Sciences
Volume
45
Issue
16
Start Page
10363
End Page
10383
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Citations
CrossRef : 3
Scopus : 6
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