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Title: Dynamic programming principle for backward doubly stochastic recursive optimal control problem and sobolev weak solution of the stochastic Hamilton-Jacobi-Bellman equation
Authors: Li, Y 
Matoussi, A
Wei, L
Wu, Z
Issue Date: 2023
Source: Fundamental research, Available online 11 December 2023, In Press, Corrected Proof, https://doi.org/10.1016/j.fmre.2023.08.014
Abstract: In this paper, we investigate a backward doubly stochastic recursive optimal control problem wherein the cost function is expressed as the solution to a backward doubly stochastic differential equation. We present the dynamical programming principle for this type of optimal control problem and establish that the value function is the unique Sobolev weak solution to the associated stochastic Hamilton-Jacobi-Bellman equation.
Keywords: Backward doubly stochastic differential equation
Dynamic programming principle
Hamilton-Jacobi-Bellman equation
Recursive optimal control
Sobolev weak solution
Publisher: National Natural Science Foundation of China
Journal: Fundamental research 
ISSN: 2096-9457
EISSN: 2667-3258
DOI: 10.1016/j.fmre.2023.08.014
Rights: © 2023 The Authors. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
The following publication Li, Y., Matoussi, A., Wei, L., & Wu, Z. (2023). Dynamic programming principle for backward doubly stochastic recursive optimal control problem and sobolev weak solution of the stochastic Hamilton-Jacobi-Bellman equation. Fundamental Research is available at https://doi.org/10.1016/j.fmre.2023.08.014.
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