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This paper presents a mathematical formulation to perform temporal parallelisation of continuous-time optimal control problems, which can be solved via the Hamilton--Jacobi--Bellman (HJB) equation. We divide the time interval of the control…

Optimization and Control · Mathematics 2024-12-18 Simo Särkkä , Ángel F. García-Fernández

The paper deals with a class of time-inconsistent control problems for McKean-Vlasov dynamics. By solving a backward time-inconsistent Hamilton-Jacobi-Bellman (HJB for short) equation coupled with a forward distribution-dependent stochastic…

Optimization and Control · Mathematics 2020-02-18 Hongwei Mei , Chao Zhu

A learning technique for finite horizon optimal control problems and its approximation based on polynomials is analyzed. It allows to circumvent, in part, the curse dimensionality which is involved when the feedback law is constructed by…

Optimization and Control · Mathematics 2023-02-21 Karl Kunisch , Donato Vásquez-Varas

We study a class of backward stochastic differential equations (BSDEs) driven by a random measure or, equivalently, by a marked point process. Under appropriate assumptions we prove well-posedness and continuous dependence of the solution…

Probability · Mathematics 2012-05-24 Fulvia Confortola , Marco Fuhrman

Continuous-time reinforcement learning offers an appealing formalism for describing control problems in which the passage of time is not naturally divided into discrete increments. Here we consider the problem of predicting the distribution…

Machine Learning · Computer Science 2022-06-20 Harley Wiltzer , David Meger , Marc G. Bellemare

Considering that the decision-making environment faced by reinforcement learning (RL) agents is full of Knightian uncertainty, this paper describes the exploratory state dynamics equation in Knightian uncertainty to study the…

Optimization and Control · Mathematics 2026-01-27 Ziyu Li , Chen Fei , Weiyin Fei

In this paper, a finite-horizon optimal control problem involving a dynamical system described by a linear Caputo fractional differential equation and a quadratic cost functional is considered. An explicit formula for the value functional…

Optimization and Control · Mathematics 2024-04-25 Mikhail I. Gomoyunov

The path-integral control, which stems from the stochastic Hamilton-Jacobi-Bellman equation, is one of the methods to control stochastic nonlinear systems. This paper gives a new insight into nonlinear stochastic optimal control problems…

Optimization and Control · Mathematics 2021-09-14 Jun Ohkubo

Feedback controllers for port-Hamiltonian systems reveal an intrinsic inverse optimality property since each passivating state feedback controller is optimal with respect to some specific performance index. Due to the nonlinear…

Optimization and Control · Mathematics 2020-07-20 Lukas Kölsch , Pol Jané Soneira , Felix Strehle , Sören Hohmann

This paper presents an inverse optimality method to solve the Hamilton-Jacobi-Bellman equation for a class of nonlinear problems for which the cost is quadratic and the dynamics are affine in the input. The method is inverse optimal because…

Optimization and Control · Mathematics 2011-10-11 Luis Rodrigues , Didier Henrion , Mehdi Abedinpour Fallah

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

In this paper, the stochastic verification theorems for stochastic control problems of reflected forward-backward stochastic differential equations are studied. We carry out the work within the frameworks of classical and viscosity…

Optimization and Control · Mathematics 2023-06-07 Lu Liu , Xinlei Hu , Qingmeng Wei

One of the fundamental issues in Control Theory is to design feedback controls. It is well-known that, the purpose of introducing Riccati equations in the deterministic case is to provide the desired feedback controls for linear quadratic…

Optimization and Control · Mathematics 2016-11-28 Qi Lu , Tianxiao Wang , Xu Zhang

In this paper we study the optimal stochastic control problem for stochastic differential systems reflected in a domain. The cost functional is a recursive one, which is defined via generalized backward stochastic differential equations…

Probability · Mathematics 2013-08-26 Juan Li , Shanjian Tang

We study the well-posedness of Hamilton-Jacobi-Bellman equations on subsets of $\mathbb{R}^d$ in a context without boundary conditions. The Hamiltonian is given as the supremum over two parts: an internal Hamiltonian depending on an…

Analysis of PDEs · Mathematics 2021-04-05 Richard C. Kraaij , Mikola C. Schlottke

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

Controlling the stochastic dynamics of biological populations is a challenge that arises across various biological contexts. However, these dynamics are inherently nonlinear and involve a discrete state space, i.e., the number of molecules,…

Populations and Evolution · Quantitative Biology 2025-10-21 Shuhei A. Horiguchi , Tetsuya J. Kobayashi

In this paper, we study the irregular output feedback linear quadratic (LQ) control problem, which is a continuous work of previous works for irregular LQ control [33] where the state is assumed to be exactly known priori. Different from…

Optimization and Control · Mathematics 2019-05-17 Juanjuan Xu , Huanshui Zhang

In this manuscript we consider a class optimal control problem for stochastic differential delay equations. First, we rewrite the problem in a suitable infinite-dimensional Hilbert space. Then, using the dynamic programming approach, we…

Optimization and Control · Mathematics 2023-02-20 Filippo de Feo , Salvatore Federico , Andrzej Święch

In standard treatments of stochastic filtering one first has to estimate the values of the parameters of the model. Simply running the filter without considering the reliability of this estimate does not take into account this additional…

Probability · Mathematics 2018-09-05 Andrew L. Allan , Samuel N. Cohen