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We introduce a framework for the control of discrete-time switched stochastic systems with uncertain distributions. In particular, we consider stochastic dynamics with additive noise whose distribution lies in an ambiguity set of…

Systems and Control · Electrical Eng. & Systems 2024-05-21 Ibon Gracia , Dimitris Boskos , Morteza Lahijanian , Luca Laurenti , Manuel Mazo

We consider the infinite-horizon average-reward restless bandit problem. We propose a novel \emph{two-set policy} that maintains two dynamic subsets of arms: one subset of arms has a nearly optimal state distribution and takes actions…

Machine Learning · Computer Science 2024-10-18 Yige Hong , Qiaomin Xie , Yudong Chen , Weina Wang

This paper examines a Markovian model for the optimal irreversible investment problem of a firm aiming at minimizing total expected costs of production. We model market uncertainty and the cost of investment per unit of production capacity…

Probability · Mathematics 2017-01-10 Tiziano De Angelis , Salvatore Federico , Giorgio Ferrari

This paper is concerned with one kind of partially observed progressive optimal control problems of coupled forward-backward stochastic systems driven by both Brownian motion and Poisson random measure with risk-sensitive criteria. The…

Optimization and Control · Mathematics 2025-04-08 Jingtao Lin , Jingtao Shi

Sharp asymptotic lower bounds of the expected quadratic variation of discretization error in stochastic integration are given. The theory relies on inequalities for the kurtosis and skewness of a general random variable which are themselves…

Probability · Mathematics 2012-04-04 Masaaki Fukasawa

We consider a multi-class G/G/1 queue with a finite shared buffer. There is task admission and server scheduling control which aims to minimize the cost which consists of holding and rejection components. We construct a policy that is…

Performance · Computer Science 2015-08-31 Mark Shifrin

We study a stochastic optimal control problem for fully coupled forward-backward stochastic control systems with a nonempty control domain. For our problem, the first-order and second-order variational equations are fully coupled linear…

Optimization and Control · Mathematics 2018-12-05 Mingshang Hu , Shaolin Ji , Xiaole Xue

We introduce a spatial economic growth model where space is described as a network of interconnected geographic locations and we study a corresponding finite-dimensional optimal control problem on a graph with state constraints. Economic…

We study the asymptotic relations between certain singular and constrained control problems for one-dimensional diffusions with both discounted and ergodic objectives. By constrained control problems we mean that controlling is allowed only…

Probability · Mathematics 2020-11-03 Jukka Lempa , Harto Saarinen

This paper is concerned with a constrained stochastic linear-quadratic optimal control problem, in which the terminal state is fixed and the initial state is constrained to lie in a stochastic linear manifold. The controllability of…

Optimization and Control · Mathematics 2019-06-11 Xiuchun Bi , Jingrui Sun , Jie Xiong

We consider the control problem of the stochastic Navier-Stokes equations in multidimensional domains introduced in \cite{ocpc} restricted to noise terms defined by Q-Wiener processes. Using a stochastic maximum principle, we derive a…

Optimization and Control · Mathematics 2018-10-30 Peter Benner , Christoph Trautwein

We consider a stochastic impulse control problem that is motivated by applications such as the optimal exploitation of a natural resource. In particular, we consider a stochastic system whose uncontrolled state dynamics are modelled by a…

Optimization and Control · Mathematics 2024-08-27 Zhesheng Liu , Mihail Zervos

This paper derives an optimal control strategy for a simple stochastic dynamical system with constant drift and an additive control input. Motivated by the example of a physical system with an unexpected change in its dynamics, we take the…

Optimization and Control · Mathematics 2022-02-09 Daniel Gurevich , Debdipta Goswami , Charles L. Fefferman , Clarence W. Rowley

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 a stochastic linear-quadratic optimal control problem with regime switching, random coefficients, and cone control constraint. The randomness of the coefficients comes from two aspects: the Brownian motion and…

Optimization and Control · Mathematics 2022-01-07 Ying Hu , Xiaomin Shi , Zuo Quan Xu

A new formulation of Stochastic Model Predictive Output Feedback Control is presented and analyzed as a translation of Stochastic Optimal Output Feedback Control into a receding horizon setting. This requires lifting the design into a…

Optimization and Control · Mathematics 2020-05-01 Martin A Sehr , Robert R Bitmead

We study data-driven learning of robust stochastic control for infinite-horizon systems with potentially continuous state and action spaces. In many managerial settings--supply chains, finance, manufacturing, services, and dynamic…

Machine Learning · Statistics 2025-11-18 Shengbo Wang , Jason Meng , Nian Si , Jose Blanchet , Zhengyuan Zhou

We derive the explicit solutions to singular stochastic control problems of the monotone follower type with (a) an expected discounted criterion, (b) an expected ergodic criterion and (c) a pathwise ergodic criterion. These problems have…

Optimization and Control · Mathematics 2025-02-05 Gechun Liang , Zhesheng Liu , Mihail Zervos

This paper studies the stabilization problem of networked control systems (NCSs) with random packet dropouts caused by stochastic channels. To describe the effects of stochastic channels on the information transmission, the transmission…

Systems and Control · Electrical Eng. & Systems 2024-01-23 Wei Ren , Wei Wang , Zhuo-Rui Pan , Xi-Ming Sun , Andrew R. Teel , Dragan Nesic

Optimal control under uncertainty is a prevailing challenge for many reasons. One of the critical difficulties lies in producing tractable solutions for the underlying stochastic optimization problem. We show how advanced approximate…

Machine Learning · Computer Science 2024-10-28 Joe Watson , Hany Abdulsamad , Rolf Findeisen , Jan Peters