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This paper develops a unified methodology for probabilistic analysis and optimal control design for jump diffusion processes defined by polynomials. For such systems, the evolution of the moments of the state can be described via a system…

Optimization and Control · Mathematics 2017-02-03 Andrew Lamperski , Khem Raj Ghusinga , Abhyudai Singh

The optimal control problem of stochastic systems is commonly solved via robust or scenario-based optimization methods, which are both challenging to scale to long optimization horizons. We cast the optimal control problem of a stochastic…

Machine Learning · Computer Science 2025-09-17 Etienne Buehrle , Christoph Stiller

We develop a classical well-posedness and regularity theory on a finite connected weighted graph for an extended mean field game system, its associated master equation, and a Hamilton-Jacobi- Bellman equation on the probability simplex, all…

Analysis of PDEs · Mathematics 2026-05-08 Wilfrid Gangbo , Sebastian Munoz , Jeremy Wu , Zhaoyu Zhang

We develop a model in two dimensions to characterise the growth rate of a tracer gradient mixed by a statistically homogeneous flow with rapid temporal variations. % % The model is based on the orientation dynamics of the passive-tracer…

Fluid Dynamics · Physics 2010-05-05 Lennon Ó Náraigh

We propose a model based on coupled multiplicative stochastic processes to understand the dynamics of competing species in an ecosystem. This process can be conveniently described by a Fokker-Planck equation. We provide an analytical…

Populations and Evolution · Quantitative Biology 2012-03-13 Simone Pigolotti , Alessandro Flammini , Amos Maritan

We study the problem of optimally managing an inventory with unknown demand trend. Our formulation leads to a stochastic control problem under partial observation, in which a Brownian motion with non-observable drift can be singularly…

Optimization and Control · Mathematics 2022-11-28 Salvatore Federico , Giorgio Ferrari , Neofytos Rodosthenous

In this work, based on the complete Bernstein function, we propose a generalized regularity analysis including maximal $\mathrm{L}^p$ regularity for the Fokker--Planck equation, which governs the subordinated Brownian motion with the…

Numerical Analysis · Mathematics 2022-06-09 Xiangong Tang , Can Wang , Weihua Deng

We analyze a problem of optimal control of the Fokker-Planck equation with state constraints in the Wasserstein space of probability measures. Our main result is to derive optimality conditions in the form of a Mean Field Game system of…

Optimization and Control · Mathematics 2023-05-16 Samuel Daudin

The aim of this contribution is to study the particle dynamics in a storage ring under the influence of noise. Some simplified stochastic beam dynamics problems are treated by solving the corresponding Fokker-Planck equations numerically.

Accelerator Physics · Physics 2009-10-31 H. Mais , M. P. Zorzano

The main purpose of this paper is to establish the first and second order necessary optimality conditions for stochastic optimal controls using the classical variational analysis approach. The control system is governed by a stochastic…

Optimization and Control · Mathematics 2016-11-09 Hélène Frankowska , Haisen Zhang , Xu Zhang

The purpose of this paper is to provide a detailed probabilistic analysis of the optimal control of nonlinear stochastic dynamical systems of the McKean Vlasov type. Motivated by the recent interest in mean field games, we highlight the…

Probability · Mathematics 2013-03-26 René Carmona , Francois Delarue

Modern energy systems in vehicles and built infrastructure are governed by high-dimensional dynamics spanning multiple physical domains (e.g., electrical, thermal, mechanical) and timescales. This tutorial paper presents a graph-based…

In this work, the primary goal is to establish rigorous connection between the Fokker-Planck equation of neural networks with its microscopic model: the diffusion-jump stochastic process that captures the mean field behavior of collections…

Analysis of PDEs · Mathematics 2021-11-01 Jian-guo Liu , Ziheng Wang , Yuan Zhang , Zhennan Zhou

This paper is addressed to studying the exact controllability for stochastic transport equations by two controls: one is a boundary control imposed on the drift term and the other is an internal control imposed on the diffusion term. By…

Optimization and Control · Mathematics 2013-10-22 Qi Lü

Optimal control of stochastic nonlinear dynamical systems is a major challenge in the domain of robot learning. Given the intractability of the global control problem, state-of-the-art algorithms focus on approximate sequential optimization…

Machine Learning · Computer Science 2020-04-23 Joe Watson , Hany Abdulsamad , Jan Peters

Active many-body systems composed of many interacting degrees of freedom often operate out of equilibrium, giving rise to non-trivial emergent behaviors which can be functional in both evolved and engineered contexts. This naturally…

Soft Condensed Matter · Physics 2023-11-29 Sumit Sinha , Vishaal Krishnan , L Mahadevan

This report provides a description of unbunched beam stochastic cooling in the framework of control theory. The main interest in the investigation is concentrated on the beam stability in an active cooling system. A stochastic cooling…

acc-phys · Physics 2008-02-03 O. Meincke

Stochastic dynamical systems provide essential mathematical frameworks for modeling complex real-world phenomena. The Fokker-Planck-Kolmogorov (FPK) equation governs the evolution of probability density functions associated with stochastic…

Computation · Statistics 2025-10-13 Yi Zhang , Yiting Duan , Xiangjun Wang , Zhikun Zhang

We formulate a data-driven method for constructing finite volume discretizations of a dynamical system's underlying Continuity / Fokker-Planck equation. A method is employed that allows for flexibility in partitioning state space,…

Fluid Dynamics · Physics 2023-04-10 Andre N. Souza

We study a stochastic control problem for nonlinear systems governed by stochastic differential equations with irregular drift. The drift coefficient is assumed to decompose as $b(t,x,a)=b_1(t,x)+b_2(x)b_3(t,a)$, where $b_1$ is bounded and…

Optimization and Control · Mathematics 2026-04-02 Antoine Marie Bogso , Rhoss Likibi Pellat , Wilfried Kuissi Kamdem , Olivier Menoukeu Pamen