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We perform a systematic study of optimization problems in the Wasserstein spaces that are analogs of infinite horizon, deterministic control problems. We derive necessary conditions on action minimizing paths and present a sufficient…

Analysis of PDEs · Mathematics 2014-06-25 Ryan Hynd , Hwa Kil Kim

This paper is devoted to a viscosity solution theory of the stochastic Hamilton-Jacobi-Bellman equation in the Wasserstein spaces for the mean-field type control problem which allows for random coefficients and may thus be non-Markovian.…

Optimization and Control · Mathematics 2023-10-24 Hang Cheung , Jinniao Qiu , Alexandru Badescu

We consider a kind of stochastic exit time optimal control problems, in which the cost function is defined through a nonlinear backward stochastic differential equation. We study the regularity of the value function for such a control…

Probability · Mathematics 2016-03-15 Rainer Buckdahn , Tianyang Nie

This work is the third part of a program initiated in arXiv:2111.13258, arXiv:2302.06571 aiming at the development of an intrinsic geometric well-posedness theory for Hamilton-Jacobi equations related to controlled gradient flow problems in…

Analysis of PDEs · Mathematics 2024-02-02 Giovanni Conforti , Richard C. Kraaij , Luca Tamanini , Daniela Tonon

Dynamic equations concerning physical expectation values have been examined in terms of the real Hilbert space approach to quantum mechanics. The considered cases involve complex wave functions, as well as quaternionic wave functions. The…

Quantum Physics · Physics 2025-09-19 Sergio Giardino

In this work we prove an analogue, for partial differential equations on the space of probability measures, of the classical vanishing viscosity result known for equations on the Euclidean space. Our result allows in particular to show that…

Probability · Mathematics 2022-06-07 Ludovic Tangpi

This paper explores the application of nonsmooth analysis in the Wasserstein space to finite-horizon optimal control problems for nonlocal continuity equations. We characterize the value function as a strict viscosity solution of the…

Optimization and Control · Mathematics 2025-04-28 Yurii Averboukh , Aleksei Volkov

This paper is devoted to solving a class of second order Hamilton-Jacobi-Bellman (HJB) equations in the Wasserstein space, associated with mean field control problems involving common noise. The well-posedness of viscosity solutions to the…

Optimization and Control · Mathematics 2024-08-28 Hang Cheung , Ho Man Tai , Jinniao Qiu

We consider an optimal control problem with ergodic (long term average) reward for a McKean-Vlasov dynamics, where the coefficients of a controlled stochastic differential equation depend on the marginal law of the solution. Starting from…

Optimization and Control · Mathematics 2025-11-25 Marco Fuhrman , Silvia Rudà

This paper continues the study of controlled interacting particle systems with common noise started in [W. Gangbo, S. Mayorga and A. \'{S}wi\k{e}ch, SIAM J. Math. Anal. 53 (2021), no. 2, 1320--1356] and [S. Mayorga and A. \'{S}wi\k{e}ch,…

Optimization and Control · Mathematics 2025-06-24 Andrzej Święch , Lukas Wessels

The aim of this article is twofold. First, we develop a unified framework for viscosity solutions to both first-order Hamilton-Jacobi equations and semilinear Hamilton-Jacobi equations driven by the idiosyncratic operator, defined on the…

Analysis of PDEs · Mathematics 2026-01-22 Giacomo Ceccherini Silberstein , Daniela Tonon

We study existence of probability measure valued jump-diffusions described by martingale problems. We develop a simple device that allows us to embed Wasserstein spaces and other similar spaces of probability measures into locally compact…

Probability · Mathematics 2020-12-03 Martin Larsson , Sara Svaluto-Ferro

Let $(S,d)$ be a compact metric space and let $m$ be a Borel probability measure on $(S,d)$. We shall prove that, if $(S,d,m)$ is a $RCD(K,\infty)$ space, then the stochastic value function satisfies the viscous Hamilton-Jacobi equation,…

Analysis of PDEs · Mathematics 2016-12-20 Ugo Bessi

In this paper, we show that the value functions of mean field control problems with common noise are the unique viscosity solutions to fully second-order Hamilton-Jacobi-Bellman equations, in a Crandall-Lions-like framework. We allow the…

Optimization and Control · Mathematics 2025-01-06 Erhan Bayraktar , Hang Cheung , Ibrahim Ekren , Jinniao Qiu , Ho Man Tai , Xin Zhang

The goal of this paper is to prove a comparison principle for viscosity solutions of semilinear Hamilton-Jacobi equations in the space of probability measures. The method involves leveraging differentiability properties of the…

Analysis of PDEs · Mathematics 2023-08-30 Samuel Daudin , Benjamin Seeger

We study a stochastic control problem on a bounded domain, which arises from a continuous-time optimal management model. Via the corresponding Hamilton-Jacobi-Bellman equation the value function is shown to be jointly continuous and to…

Probability · Mathematics 2017-10-24 Ruoting Gong , Christian Houdré

We investigate the large-time behavior of the value functions of the optimal control problems on the $n$-dimensional torus which appear in the dynamic programming for the system whose states are governed by random changes. From the point of…

Analysis of PDEs · Mathematics 2013-03-13 Hiroyoshi Mitake , Hung V. Tran

We develop a gradient-flow theory for time-dependent functionals defined in abstract metric spaces. Global well-posedness and asymptotic behavior of solutions are provided. Conditions on functionals and metric spaces allow to consider the…

Analysis of PDEs · Mathematics 2015-09-15 Lucas C. F. Ferreira , Julio C. Valencia-Guevara

We consider the dynamics of a Hamiltonian particle forced by a rapidly oscillating potential in $\dim$-dimensional space. As alternative to the established approach of averaging Hamiltonian dynamics by reformulating the system as…

Dynamical Systems · Mathematics 2018-09-13 Hartmut Schwetlick , Daniel C. Sutton , Johannes Zimmer

We develop a framework for generalized variational inference in infinite-dimensional function spaces and use it to construct a method termed Gaussian Wasserstein inference (GWI). GWI leverages the Wasserstein distance between Gaussian…

Machine Learning · Statistics 2022-10-18 Veit D. Wild , Robert Hu , Dino Sejdinovic
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