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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

In this paper, we consider the gradual-impulse control problem of continuous-time Markov decision processes, where the system performance is measured by the expectation of the exponential utility of the total cost. We prove, under very…

Optimization and Control · Mathematics 2023-11-16 Xin Guo , Aiko Kurushima , Alexey Piunovskiy , Yi Zhang

Optimal control problems involving hybrid binary-continuous control costs are challenging due to their lack of convexity and weak lower semicontinuity. Replacing such costs with their convex relaxation leads to a primal-dual optimality…

Optimization and Control · Mathematics 2017-02-27 Christian Clason , Kazufumi Ito , Karl Kunisch

This paper is concerned with a discounted optimal control problem of partially observed forward-backward stochastic systems with jumps on infinite horizon. The control domain is convex and a kind of infinite horizon observation equation is…

Optimization and Control · Mathematics 2022-01-04 Yueyang Zheng , Jingtao Shi

This paper is concerned with a stochastic linear quadratic (LQ, for short) control problem with a recursive cost functional. It involves BSDEs in $L^1$ whose well-posedness is a subtle issue. A suitable framework has been adopted so that…

Optimization and Control · Mathematics 2026-01-30 Lin Li , Jiongmin Yong

This paper is concerned with stochastic linear quadratic (LQ, for short) optimal control problems in an infinite horizon with conditional mean-field term in a switching regime environment. The orthogonal decomposition introduced in [21] has…

Optimization and Control · Mathematics 2025-01-03 Hongwei Mei , Qingmeng Wei , Jiongmin Yong

In this letter, we study a Networked Control System (NCS) with multiplexed communication and Bernoulli packet drops. Multiplexed communication refers to the constraint that transmission of a control signal and an observation signal cannot…

Systems and Control · Electrical Eng. & Systems 2024-09-04 Harsh Oza , Irinel-Constantin Morarescu , Vineeth S. Varma , Ravi Banavar

This paper is concerned with a stochastic linear quadratic (LQ, for short) control problem with a recursive cost functional in an infinite horizon. A main difficult is well-posedness of the BSDE in $L^1$ and in infinite horizon. A notion of…

Optimization and Control · Mathematics 2026-05-07 Lin Li , Jiongmin Yong

Time estimation is a fundamental task that underpins precision measurement, global navigation systems, financial markets, and the organisation of everyday life. Many biological processes also depend on time estimation by nanoscale clocks,…

Control loops closed over wireless links greatly benefit from accurate estimates of the communication channel condition. To this end, the finite-state Markov channel model allows for reliable channel state estimation. This paper develops a…

Systems and Control · Electrical Eng. & Systems 2025-06-13 Yuriy Zacchia Lun , Francesco Smarra , Alessandro D'Innocenzo

The paper provides an overview of the theory and applications of risk-sensitive Markov decision processes. The term 'risk-sensitive' refers here to the use of the Optimized Certainty Equivalent as a means to measure expectation and risk.…

Risk Management · Quantitative Finance 2025-09-23 Nicole Bäuerle , Anna Jaśkiewicz

This paper considers the problem of partially observed optimal control for forward stochastic systems which are driven by Brownian motions and an independent Poisson random measure with a feature that the cost functional is of mean-field…

Probability · Mathematics 2014-03-19 Yaozhong Hu , David Nualart , Qing Zhou

In this paper, we concern with the ergodic linear-quadratic closed-loop optimal control problems, in which the state equation is the mean-field stochastic differential equation with periodic coefficients. We first study the asymptotic…

Optimization and Control · Mathematics 2025-05-09 Jiacheng Wu , Qi Zhang

This paper shows that the optimal policy and value functions of a Markov Decision Process (MDP), either discounted or not, can be captured by a finite-horizon undiscounted Optimal Control Problem (OCP), even if based on an inexact model.…

Systems and Control · Electrical Eng. & Systems 2023-02-08 Arash Bahari Kordabad , Mario Zanon , Sebastien Gros

In this paper, we present a generalization of the certainty equivalence principle of stochastic control. One interpretation of the classical certainty equivalence principle for linear systems with output feedback and quadratic costs is as…

Optimization and Control · Mathematics 2026-02-04 Berk Bozkurt , Aditya Mahajan , Ashutosh Nayyar , Yi Ouyang

We provide a method to design adaptive controllers for nonlinear systems using model predictive control (MPC). By combining a certainty-equivalent MPC formulation with least-mean-square parameter adaptation, we obtain an adaptive controller…

Optimization and Control · Mathematics 2026-03-19 Johannes Köhler

Stochastic and soft optimal policies resulting from entropy-regularized Markov decision processes (ER-MDP) are desirable for exploration and imitation learning applications. Motivated by the fact that such policies are sensitive with…

Machine Learning · Computer Science 2022-01-03 Tien Mai , Patrick Jaillet

This paper is concerned with a kind of linear-quadratic (LQ) optimal control problem of backward stochastic differential equation (BSDE) with partial information. The cost functional includes cross terms between the state and control, and…

Optimization and Control · Mathematics 2025-09-03 Jialong Li , Zhiyong Yu , Wanying Yue

An optimal ergodic control problem (EC problem, for short) is investigated for a linear stochastic differential equation with quadratic cost functional. Constant nonhomogeneous terms, not all zero, appear in the state equation, which lead…

Optimization and Control · Mathematics 2020-04-24 Hongwei Mei , Qingmeng Wei , Jiongmin Yong

Relative fluctuations of observables in discrete stochastic systems are bounded at all times by the mean dynamical activity in the system, quantified by the mean number of jumps. This constitutes a kinetic uncertainty relation that is…

Statistical Mechanics · Physics 2019-01-08 Ivan Di Terlizzi , Marco Baiesi