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In this paper we study the fully nonlinear stochastic Hamilton-Jacobi-Bellman (HJB) equation for the optimal stochastic control problem of stochastic differential equations with random coefficients. The notion of viscosity solution is…

Optimization and Control · Mathematics 2018-07-16 Jinniao Qiu

In the paper, we use the equivalent formulation of a finite state mean field game as a control problem with mixed constraints to study the dependence of solutions to finite state mean field game on an initial distribution of players. We…

Optimization and Control · Mathematics 2021-09-16 Yurii Averboukh

In this paper, we study one kind of stochastic recursive optimal control problem with the obstacle constraints for the cost function where the cost function is described by the solution of one reflected backward stochastic differential…

Optimization and Control · Mathematics 2007-05-23 Zhen Wu , Zhiyong Yu

We consider the control of McKean-Vlasov dynamics (or mean-field control) with probabilistic state constraints. We rely on a level-set approach which provides a representation of the constrained problem in terms of an unconstrained one with…

Optimization and Control · Mathematics 2022-11-03 Maximilien Germain , Huyên Pham , Xavier Warin

In this paper we are interested in a new type of {\it mean-field}, non-Markovian stochastic control problems with partial observations. More precisely, we assume that the coefficients of the controlled dynamics depend not only on the paths…

Probability · Mathematics 2017-02-21 Rainer Buckdahn , Juan Li , Jin Ma

A general and new stochastic linear quadratic optimal control problem is studied, where the coefficients are allowed to be time-varying, and both state delay and control delay can appear simultaneously in the state equation and the cost…

Optimization and Control · Mathematics 2026-02-24 Weijun Meng , Tianxiao Wang , Ji-Feng Zhang

We describe a nonlinear generalization of dual dynamic programming theory and its application to value function estimation for deterministic control problems over continuous state and action spaces, in a discrete-time infinite horizon…

Optimization and Control · Mathematics 2018-10-05 Joseph Warrington , Paul N. Beuchat , John Lygeros

The traditional difficulty about stochastic singular control is to characterize the regularities of the value function and the optimal control policy. In this paper, a multi-dimensional singular control problem is considered. We found the…

Optimization and Control · Mathematics 2014-06-17 Yipeng Yang

In this manuscript we consider optimal control problems of stochastic differential equations with delays in the state and in the control. First, we prove an equivalent Markovian reformulation on Hilbert spaces of the state equation. Then,…

Optimization and Control · Mathematics 2024-05-20 Filippo de Feo

This paper analyses a stochastic differential game of control and stopping in which one of the players modifies a diffusion process using impulse controls, an adversary then chooses a stopping time to end the game. The paper firstly…

Optimization and Control · Mathematics 2019-10-04 David Mguni

Motivated by parallels between mean field games and random matrix theory, we develop stochastic optimal control problems and viscosity solutions to Hamilton-Jacobi equations in the setting of non-commutative variables. Rather than real…

Analysis of PDEs · Mathematics 2025-02-25 Wilfrid Gangbo , David Jekel , Kyeongsik Nam , Aaron Z. Palmer

This article is the starting point of a series of works whose aim is the study of deterministic control problems where the dynamic and the running cost can be completely different in two (or more) complementary domains of the space $\R^N$.…

Analysis of PDEs · Mathematics 2012-09-12 Guy Barles , Ariela Briani , Emmanuel Chasseigne

We investigate the continuous-time Markowitz mean-variance portfolio selection problem within a multivariate class of fake stationary affine Volterra models. In this non-Markovian and non-semimartingale market framework with unbounded…

Optimization and Control · Mathematics 2026-04-03 Emmanuel Gnabeyeu

An effective form of the Variation Evolving Method (VEM), which originates from the continuous-time dynamics stability theory, is developed for the classic time-optimal control problem with control constraint. Within the mathematic…

Systems and Control · Computer Science 2017-11-09 Sheng Zhang , Wei-Qi Qian

We consider a Bolza-type optimal control problem for a dynamical system described by a fractional differential equation with the Caputo derivative of an order $\alpha \in (0, 1)$. The value of this problem is introduced as a functional in a…

Optimization and Control · Mathematics 2019-08-06 Mikhail I. Gomoyunov

This paper considers the synthesis of optimal safe controllers based on density functions. We present an algorithm for robust constrained optimal control synthesis using the duality relationship between the density function and the value…

Optimization and Control · Mathematics 2019-09-30 Yuxiao Chen , Mohamadreza Ahmadi , Aaron D. Ames

This paper focuses on the role of a government of a large population of interacting agents as a mean field optimal control problem derived from deterministic finite agent dynamics. The control problems are constrained by a PDE of…

Analysis of PDEs · Mathematics 2020-11-17 Massimo Fornasier , Stefano Lisini , Carlo Orrieri , Giuseppe Savaré

We study analogs of value functions arising in classical mechanics in the space of probability measures endowed with the Wasserstein metric $W_p$, for $1<p<\infty$. Our main result is that each of these generalized value functions is a type…

Analysis of PDEs · Mathematics 2015-05-12 Ryan Hynd , Hwa Kil Kim

We consider a zero-sum stochastic differential controller-and-stopper game in which the state process is a controlled diffusion evolving in a multi-dimensional Euclidean space. In this game, the controller affects both the drift and the…

Optimization and Control · Mathematics 2013-01-15 Erhan Bayraktar , Yu-Jui Huang

We construct an abstract framework in which the dynamic programming principle (DPP) can be readily proven. It encompasses a broad range of common stochastic control problems in the weak formulation, and deals with problems in the…

Optimization and Control · Mathematics 2019-06-04 Roman Fayvisovich , Gordan Zitkovic