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This paper is concerned with the existence of optimal controls for backward stochastic partial differential equations with random coefficients, in which the control systems are represented in an abstract evolution form, i.e. backward…

Optimization and Control · Mathematics 2016-12-07 Qingxin Meng , Yang Shen , Peng Shi

This paper is concerned with optimal control of systems driven by G-stochastic differential equations (G-SDEs), with controlled jump term. We study the relaxed problem, in which admissible controls are measurevalued processes and the state…

Optimization and Control · Mathematics 2021-11-04 Hanane Ben Gherbal , Amel Redjil , Omar Kebiri

In this paper, we derive a version of the Pontryagin maximum principle for general finite-dimensional nonlinear optimal sampled-data control problems. Our framework is actually much more general, and we treat optimal control problems for…

Optimization and Control · Mathematics 2015-12-09 Loïc Bourdin , Emmanuel Trélat

The objective of the present paper is to investigate the solution of fully coupled mean-field forward-backward stochastic differential equations (FBSDEs in short) and to study the stochastic control problems of mean-field type as well as…

Optimization and Control · Mathematics 2012-07-19 Ruimin Xu , Liangquan Zhang

This paper presents a stochastic model predictive control approach for nonlinear systems subject to time-invariant probabilistic uncertainties in model parameters and initial conditions. The stochastic optimal control problem entails a cost…

Optimization and Control · Mathematics 2014-10-17 Stefan Streif , Matthias Karl , Ali Mesbah

Devising optimal interventions for constraining stochastic systems is a challenging endeavour that has to confront the interplay between randomness and nonlinearity. Existing methods for identifying the necessary dynamical adjustments…

Statistical Mechanics · Physics 2022-10-18 Dimitra Maoutsa , Manfred Opper

We introduce a new method, stepwise method for solving optimal con- trol problems. Our first motivation for new approach emanate from limi- tations on continuous time control functions in PMP. Practically in most of the real world models,…

Optimization and Control · Mathematics 2015-06-26 Mehdi Afshar , Farshad Merrikhbayat , Mohammad Reza Razvan

In this article, we consider a weighted mean-field control problem with jump-diffusion as its state process. The main difficulty is from the non-Lipschitz property of the coefficients. We overcome this difficulty by an $L_{p,q}$-estimate of…

Optimization and Control · Mathematics 2025-09-12 Yanyan Tang , Jie Xiong

In this paper, we propose a unified stochastic optimal control framework that integrates time-optimal control problems with classical stochastic optimal control formulations. Unlike conventional deterministic time-optimal control models,…

Optimization and Control · Mathematics 2025-10-21 Shuzhen Yang

In this article we derive a strong version of the Pontryagin Maximum Principle for general nonlinear optimal control problems on time scales in finite dimension. The final time can be fixed or not, and in the case of general boundary…

Optimization and Control · Mathematics 2013-02-15 Loïc Bourdin , Emmanuel Trélat

Guidance is a cornerstone of modern diffusion models, playing a pivotal role in conditional generation and enhancing the quality of unconditional samples. However, current approaches to guidance scheduling--determining the appropriate…

In this paper we study strongly robust optimal control problems under volatility uncertainty. In the $G$-framework we adapt the stochastic maximum principle to find necessary and sufficient conditions for the existence of a strongly robust…

Optimization and Control · Mathematics 2014-04-14 Francesca Biagini , Thilo Meyer-Brandis , Bernt Øksendal , Krzysztof Paczka

In this paper, we establish some second order necessary/sufficient optimality conditions for optimal control problems of stochastic evolution equations in infinite dimensions. The control acts on both the drift and diffusion terms and the…

Optimization and Control · Mathematics 2018-11-20 Qi Lu , Haisen Zhang , Xu Zhang

This paper deals with a stochastic optimal feedback control problem for the controlled stochastic partial differential equations. More precisely, we establish the existence of stochastic optimal feedback control for the controlled…

Probability · Mathematics 2025-01-07 Gaofeng Zong

We study time-inconsistent recursive stochastic control problems, i.e., for which the Bellman principle of optimality does not hold. For this class of problems classical optimal controls may fail to exist, or to be relevant in practice, and…

Optimization and Control · Mathematics 2024-03-14 Elisa Mastrogiacomo , Marco Tarsia

In this paper, we consider optimal control of stochastic differential equations subject to an expected path constraint. The stochastic maximum principle is given for a general optimal stochastic control in terms of constrained FBSDEs. In…

Optimization and Control · Mathematics 2022-08-16 Ying Hu , Shanjian Tang , Zuo Quan Xu

Based on Pontryagin Maximum Principle (PMP), this paper established a generalized PMP aiming at non-feedback control system with stochastic initial conditions. We proved the conclusion and show its coming back to PMP when the randomness…

Optimization and Control · Mathematics 2015-05-05 Yuanzun Zhao

In this paper, we investigate the controlled system described by forward-backward stochastic differential equations with the control contained in drift, diffusion and generator of BSDE. A new verification theorem is derived within the…

Optimization and Control · Mathematics 2012-05-28 Liangquan Zhang

This paper investigates the robustness of stochastic optimal control for controlled regime switching diffusions. We consider systems driven by both continuous fluctuations and discrete regime changes, allowing for model misspecification in…

Optimization and Control · Mathematics 2025-11-24 Somnath Pradhan , Dinesh Rathia

We propose a novel reformulation of the stochastic optimal control problem as an approximate inference problem, demonstrating, that such a interpretation leads to new practical methods for the original problem. In particular we characterise…

Machine Learning · Computer Science 2010-09-22 Konrad Rawlik , Marc Toussaint , Sethu Vijayakumar
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