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This paper deals with the general discounted impulse control problem of a piecewise deterministic Markov process. We investigate a new family of epsilon-optimal strategies. The construction of such strategies is explicit and only…

Probability · Mathematics 2016-03-28 Benoîte de Saporta , François Dufour , Alizée Geeraert

This paper deals with the finite horizon optimal control problem for discrete-time Markov jump linear system with input delay. The correlation among the jumping parameters and the input delay are considered simultaneously, which forms the…

Optimization and Control · Mathematics 2018-08-22 Chunyan Han , Hongdan Li , Huanshui Zhang

Throughout this paper, we focused our aim on the problem of optimal control under a risk-sensitive performance functional, where the system is given by a fully coupled forward-backward stochastic differential equation with jump. The risk…

Optimization and Control · Mathematics 2019-03-07 Rania Khallout , Adel Chala

In this paper, we introduce a model-based deep-learning approach to solve finite-horizon continuous-time stochastic control problems with jumps. We iteratively train two neural networks: one to represent the optimal policy and the other to…

Machine Learning · Computer Science 2026-01-16 Patrick Cheridito , Jean-Loup Dupret , Donatien Hainaut

In this paper we investigate a kind of optimal control problem of coupled forward-backward stochastic system with jumps whose cost functional is defined through a coupled forward-backward stochastic differential equation with Brownian…

Probability · Mathematics 2020-09-15 Qian Lin

We present a new, tractable method for solving and analyzing risk-aware control problems over finite and infinite, discounted time-horizons where the dynamics of the controlled process are described as a martingale problem. Supposing…

Optimization and Control · Mathematics 2020-06-23 Jukka Isohätälä , William B. Haskell

We study a discounted singular stochastic control problem driven by a general L\'evy process, where the objective is to minimize a cost functional composed of a running cost and a control cost that depends on the current state of the…

Optimization and Control · Mathematics 2026-05-18 Mordecki Ernesto , Muler Nora , Oliú Facundo

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

In most real cases transition probabilities between operational modes of Markov jump linear systems cannot be computed exactly and are time-varying. We take into account this aspect by considering Markov jump linear systems where the…

Systems and Control · Computer Science 2021-03-22 Y. Zacchia Lun , A. Abate , A. D'Innocenzo

We consider a novel queuing problem where the decision-maker must choose to accept or reject randomly arriving tasks into a no buffer queue which are processed by $N$ identical servers. Each task has a price, which is a positive real…

Machine Learning · Computer Science 2022-03-16 Marc Rigter , Danial Dervovic , Parisa Hassanzadeh , Jason Long , Parisa Zehtabi , Daniele Magazzeni

This paper is concerned with stochastic impulse control problems in which the running cost changes depending on the impulse control. Because of such a dependence, it brings several difficulties when the usual dynamic programming principle…

Optimization and Control · Mathematics 2025-11-11 Yuchen Cao , Jiongmin Yong

This article considers the average optimality for a continuous-time Markov decision process with Borel state and action spaces and an arbitrarily unbounded nonnegative cost rate. The existence of a deterministic stationary optimal policy is…

Optimization and Control · Mathematics 2014-03-05 Yi Zhang

This paper first describes a class of uncertain stochastic control systems with Markovian switching, and derives an It\^o-Liu formula for Markov-modulated processes. And we characterize an optimal control law, which satisfies the…

Optimization and Control · Mathematics 2014-01-14 Weiyin Fei

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

In this paper we study a class of stochastic control problems in which the control of the jump size is essential. Such a model is a generalized version for various applied problems ranging from optimal reinsurance selections for general…

Probability · Mathematics 2008-04-04 Rainer Buckdahn , Jin Ma , Catherine Rainer

In the present work we employ, for the first time, backward stochastic differential equations (BSDEs) to study the optimal control of semi-Markov processes on finite horizon, with general state and action spaces. More precisely, we prove…

Optimization and Control · Mathematics 2015-05-27 Elena Bandini , Fulvia Confortola

There are no computationally feasible algorithms that provide solutions to the finite horizon Risk-sensitive Constrained Markov Decision Process (Risk-CMDP) problem, even for problems with moderate horizon. With an aim to design the same,…

Optimization and Control · Mathematics 2023-03-27 Vartika Singh , Veeraruna Kavitha

This paper is concerned with a stochastic recursive optimal control problem with time delay, where the controlled system is described by a stochastic differential delayed equation (SDDE) and the cost functional is formulated as the solution…

Optimization and Control · Mathematics 2014-08-26 Jingtao Shi , Huanshui Zhang

We consider an infinite horizon discounted optimal control problem for piecewise deterministic Markov processes, where a piecewise open-loop control acts continuously on the jump dynamics and on the deterministic flow. For this class of…

Optimization and Control · Mathematics 2015-12-08 Elena Bandini

We consider the problem of maximizing expected utility for a power investor who can allocate his wealth in a stock, a defaultable security, and a money market account. The dynamics of these security prices are governed by geometric Brownian…

Portfolio Management · Quantitative Finance 2014-06-04 Agostino Capponi , Jose Enrique Figueroa Lopez , Andrea Pascucci