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Related papers: Optimal Control of McKean--Vlasov Branching Diffus…

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We study a family of McKean-Vlasov (mean-field) type ergodic optimal control problems with linear control, and quadratic dependence on control of the cost function. For this class of problems we establish existence and uniqueness of an…

Probability · Mathematics 2021-05-26 Sergio Albeverio , Francesco C. De Vecchi , Andrea Romano , Stefania Ugolini

We study a regulation problem for stochastic systems subject to both continuous fluctuations and rare but significant shocks, modeled as a jump-diffusion with uncertainty in both the drift and the jump intensity. Such settings arise in…

Optimization and Control · Mathematics 2026-05-26 Abel Azze , Bernardo D'Auria , Giorgio Ferrari

We consider the problem of stochastic optimal control, where the state-feedback control policies take the form of a probability distribution and where a penalty on the entropy is added. By viewing the cost function as a Kullback- Leibler…

Optimization and Control · Mathematics 2024-12-12 Marc Lambert , Francis Bach , Silvère Bonnabel

We study long-term growth-optimal strategies on a simple market with linear proportional transaction costs. We show that several problems of this sort can be solved in closed form, and explicit the non-analytic dependance of optimal…

Statistical Mechanics · Physics 2011-06-24 Erik Aurell , Paolo Muratore-Ginanneschi

The present paper considers a stochastic optimal control problem, in which the cost function is defined through a backward stochastic differential equation with infinite horizon driven by G-Brownian motion. Then we study the regularities of…

Probability · Mathematics 2017-06-13 Mingshang Hu , Falei Wang

This paper studies the stochastic optimal control of jump-diffusion processes and the associated fully nonlinear backward stochastic Hamilton--Jacobi--Bellman (BSHJB) equations. We establish the dynamic programming principle (DPP) via…

Optimization and Control · Mathematics 2026-05-21 Dunxiang Liang , Qingxin Meng

We consider the infinite horizon risk-sensitive problem for nondegenerate diffusions with a compact action space, and controlled through the drift. We only impose a structural assumption on the running cost function, namely…

Optimization and Control · Mathematics 2019-03-20 Ari Arapostathis , Anup Biswas

We study a finite horizon optimal control problem for the continuity equation under a weighted integral state constraint on the mass outside a fixed set. The model is cast in a Hilbert framework for densities. On a suitable invariant…

Optimization and Control · Mathematics 2026-04-03 Fabio Bagagiolo , Ivan Romanò

This paper focuses on the value function in the time-optimal problem for a continuity equation in the space of probability measures. We derive the dynamic programming principle for this problem. In particular, we prove that the Kruzhkov…

Analysis of PDEs · Mathematics 2026-03-03 Yurii Averboukh , Ekaterina Kolpakova

We examine the minimization of a quadratic cost functional composed of the output and the final state of abstract infinite-dimensional evolution equations in view of existence of solutions and optimality conditions. While the initial value…

Optimization and Control · Mathematics 2024-12-20 Timo Reis , Manuel Schaller

We consider a class of optimal control problems, with finite or infinite horizon, for a continuous-time Markov chain with finite state space. In this case, the control process affects the transition rates. We suppose that the controlled…

Optimization and Control · Mathematics 2026-02-19 Fulvia Confortola , Marco Fuhrman

In this paper, we investigate a distributed optimal control problem for a convective viscous Cahn-Hilliard system with dynamic boundary conditions. Such systems govern phase separation processes between two phases taking place in an…

Analysis of PDEs · Mathematics 2017-09-08 Pierluigi Colli , Gianni Gilardi , Jürgen Sprekels

We provide a new version of the Tikhonov theorem for both two-scale forward systems and also two-scale forward-backward systems of stochastic differential equations, which also covers the McKean-Vlasov case. Differently from what is usually…

Probability · Mathematics 2024-03-26 Matteo Burzoni , Alekos Cecchin , Andrea Cosso

This paper deals with a stochastic recursive optimal control problem, where the diffusion coefficient depends on the control variable and the control domain is not necessarily convex. We focus on the connection between the general maximum…

Optimization and Control · Mathematics 2016-12-21 Tianyang Nie , Jingtao Shi , Zhen Wu

In this work, we investigate a stochastic control framework for global optimization over both Euclidean spaces and the Wasserstein space of probability measures, where the objective function may be non-convex and/or non-differentiable. In…

Optimization and Control · Mathematics 2026-04-21 Jinniao Qiu

The problem of identifying the diffusion parameter appearing in a nonlocal steady diffusion equation is considered. The identification problem is formulated as an optimal control problem having a matching functional as the objective of the…

Optimization and Control · Mathematics 2015-02-03 Marta D'Elia , Max Gunzburger

In this paper, we consider the stochastic optimal control problem for jump diffusion systems with state constraints. In general, the value function of such problems is a discontinuous viscosity solution of the Hamilton-Jacobi-Bellman (HJB)…

Optimization and Control · Mathematics 2020-06-11 Jun Moon

We consider the problem of rare event importance sampling, where the random variable of interest is a path functional of an It\^o diffusion computed up to the first exit from a $d$-dimensional bounded domain. Dupuis and Wang (\textit{Ann.…

Optimization and Control · Mathematics 2016-03-21 Han Cheng Lie

In this paper, we study the optimal singular controls for stochastic recursive systems, in which the control has two components: the regular control, and the singular control. Under certain assumptions, we establish the dynamic programming…

Optimization and Control · Mathematics 2018-11-06 Liangquan Zhang

Optimized certainty equivalents (OCEs) is a family of risk measures widely used by both practitioners and academics. This is mostly due to its tractability and the fact that it encompasses important examples, including entropic risk…

Optimization and Control · Mathematics 2022-06-07 Julio Backhoff Veraguas , A. Max Reppen , Ludovic Tangpi