Causal Hamilton-Jacobi-Bellman Equations for Anticipative Stochastic Optimal Control

We consider a stochastic optimal control problem where the controller can anticipate the evolution of the driving noise over some dynamically changing time window. The controlled state dynamics are understood as a rough differential equation. We combine the martingale optimality principle with a functional form of Itô's formula to derive a Hamilton-Jacobi-Bellman (HJB) equation for this problem. This HJB equation is formulated in terms of Dupire's functional derivatives and involves a transport equation arising from the anticipativity of the problem.

Publication Details

Journal
ArXiv.org
Published
2025-07-11
Primary Topic
Advanced Proteomics Techniques and Applications
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article

Causal Hamilton-Jacobi-Bellman Equations for Anticipative Stochastic Optimal Control

ArXiv.org
Advanced Proteomics Techniques and Applications
article

Causal Hamilton-Jacobi-Bellman Equations for Anticipative Stochastic Optimal Control

article en

Abstract

We consider a stochastic optimal control problem where the controller can anticipate the evolution of the driving noise over some dynamically changing time window. The controlled state dynamics are understood as a rough differential equation. We combine the martingale optimality principle with a functional form of Itô's formula to derive a Hamilton-Jacobi-Bellman (HJB) equation for this problem. This HJB equation is formulated in terms of Dupire's functional derivatives and involves a transport equation arising from the anticipativity of the problem.

ArXiv.org
Openalex Percentile: Top 55%
Advanced Proteomics Techniques and Applications
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Causal Hamilton-Jacobi-Bellman Equations for Anticipative Stochastic Optimal Control · ArXiv.org (2025) | TGRS Research Map | TGRS