Optimal control of McKean-Vlasov systems under partial observation and hidden Markov switching

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Fuhrman, Marco, Pham, Huyên, Ruda, Silvia
Natura: Preprint
Pubblicazione: 2026
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866917203706642432
author Fuhrman, Marco
Pham, Huyên
Ruda, Silvia
author_facet Fuhrman, Marco
Pham, Huyên
Ruda, Silvia
contents We study a class of mean-field control problems under partial observation. The controlled dynamics are of McKean-Vlasov type and are subject to regime switching driven by a hidden Markov chain. The observation process depends on the control and on the joint distribution of the state and control, which prevents the direct application of standard filtering techniques. The main contribution of this paper is to show how this distribution dependence can be handled within a change-of-probability framework, leading to a well-posed separated control problem. We derive a Zakai equation with a specific structure for the unnormalized filter, and show that the corresponding value function satisfies a dynamic programming principle. This yields a Bellman equation posed on a convex subset of a Wasserstein space, characterizing the optimal control problem under partial observation.
format Preprint
id arxiv_https___arxiv_org_abs_2601_09311
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Optimal control of McKean-Vlasov systems under partial observation and hidden Markov switching
Fuhrman, Marco
Pham, Huyên
Ruda, Silvia
Optimization and Control
Probability
We study a class of mean-field control problems under partial observation. The controlled dynamics are of McKean-Vlasov type and are subject to regime switching driven by a hidden Markov chain. The observation process depends on the control and on the joint distribution of the state and control, which prevents the direct application of standard filtering techniques. The main contribution of this paper is to show how this distribution dependence can be handled within a change-of-probability framework, leading to a well-posed separated control problem. We derive a Zakai equation with a specific structure for the unnormalized filter, and show that the corresponding value function satisfies a dynamic programming principle. This yields a Bellman equation posed on a convex subset of a Wasserstein space, characterizing the optimal control problem under partial observation.
title Optimal control of McKean-Vlasov systems under partial observation and hidden Markov switching
topic Optimization and Control
Probability
url https://arxiv.org/abs/2601.09311