Optimal Control of McKean--Vlasov Branching Diffusion Processes

Fuente: arXiv
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Main Authors: Claisse, Julien, Kang, Jiazhi, Lan, Tianxu, Tan, Xiaolu
Format: Preprint
Published: 2025
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author Claisse, Julien
Kang, Jiazhi
Lan, Tianxu
Tan, Xiaolu
author_facet Claisse, Julien
Kang, Jiazhi
Lan, Tianxu
Tan, Xiaolu
contents We study an optimal control problem of McKean--Vlasov branching diffusion processes, in which the interaction term is determined by the marginal measure induced by all alive particles in the system. Accordingly, the value function is defined on the space of finite nonnegative measures over the Euclidean space. Within the framework of Lipschitz continuous closed-loop controls, and by using the uniqueness of solution to the associated nonlinear Fokker--Planck equation, we establish the dynamic programming principle. Further, under the regularity assumptions, we show that the value function satisfies a Hamilton--Jacobi--Bellman (HJB) master equation defined on the space of finite nonnegative measures. We next provide a corresponding verification theorem. Finally, we study a linear--quadratic controlled branching processes problem, for which explicit solutions are derived in terms of Riccati-type equations.
format Preprint
id arxiv_https___arxiv_org_abs_2512_00633
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimal Control of McKean--Vlasov Branching Diffusion Processes
Claisse, Julien
Kang, Jiazhi
Lan, Tianxu
Tan, Xiaolu
Optimization and Control
Probability
We study an optimal control problem of McKean--Vlasov branching diffusion processes, in which the interaction term is determined by the marginal measure induced by all alive particles in the system. Accordingly, the value function is defined on the space of finite nonnegative measures over the Euclidean space. Within the framework of Lipschitz continuous closed-loop controls, and by using the uniqueness of solution to the associated nonlinear Fokker--Planck equation, we establish the dynamic programming principle. Further, under the regularity assumptions, we show that the value function satisfies a Hamilton--Jacobi--Bellman (HJB) master equation defined on the space of finite nonnegative measures. We next provide a corresponding verification theorem. Finally, we study a linear--quadratic controlled branching processes problem, for which explicit solutions are derived in terms of Riccati-type equations.
title Optimal Control of McKean--Vlasov Branching Diffusion Processes
topic Optimization and Control
Probability
url https://arxiv.org/abs/2512.00633