English
Related papers

Related papers: Optimal probabilities and controls for reflecting …

200 papers

Consider a set of discounted optimal stopping problems for a one-parameter family of objective functions and a fixed diffusion process, started at a fixed point. A standard problem in stochastic control/optimal stopping is to solve for the…

Probability · Mathematics 2010-05-04 David Hobson , Martin Klimmek

In this paper we consider non convex control problems of stochastic differential equations driven by relaxed controls. We present existence of optimal controls and then develop necessary conditions of optimality. We cover both continuous…

Optimization and Control · Mathematics 2013-02-15 Nasir U. Ahmed , Charalambos D. Charalambous

We study the problem of learning the optimal control policy for fine-tuning a given diffusion process, using general value function approximation. We develop a new class of algorithms by solving a variational inequality problem based on the…

Machine Learning · Computer Science 2025-09-03 Wenlong Mou

We study a stochastic optimal control problem for a partially observed diffusion. By using the control randomization method in [4], we prove a corresponding randomized dynamic programming principle (DPP) for the value function, which is…

Probability · Mathematics 2016-09-12 Elena Bandini , Andrea Cosso , Marco Fuhrman , Huyên Pham

In this paper, we consider a risk-averse control problem for diffusion processes, in which there is a partition of the admissible control strategy into two decision-making groups (namely, the {\it leader} and {\it follower}) with different…

Optimization and Control · Mathematics 2018-01-03 Getachew K. Befekadu , Alexander Veremyev , Eduardo L. Pasiliao

This work investigates the optimal control problem for reflected McKean-Vlasov SDEs and the viscosity solutions to Hamilton-Jacobi-Bellman(HJB) equations on the Wasserstein space in terms of intrinsic derivative. It follows from the flow…

Probability · Mathematics 2023-09-18 Jinghai Shao

This paper is devoted to the stochastic optimal control problem of infinite-dimensional differential systems allowing for both path-dependence and measurable randomness. As opposed to the deterministic path-dependent cases studied by…

Optimization and Control · Mathematics 2023-07-19 Jinniao Qiu , Yang Yang

We address the problem of making a managerial decision when the investment project is subsidized, which results in the resolution of an infinite-horizon optimal stopping problem of a switching diffusion driven by either an homogeneous or an…

Probability · Mathematics 2018-02-28 Carlos Oliveira , Nicolas Perkowski

We introduce and study a new class of optimal switching problems, namely switching problem with controlled randomisation, where some extra-randomness impacts the choice of switching modes and associated costs. We show that the optimal value…

Probability · Mathematics 2020-01-31 Cyril Bénézet , Jean-François Chassagneux , Adrien Richou

We study the optimal financing and dividend distribution problem with restricted dividend rates in a diffusion type surplus model where the drift and volatility coefficients are general functions of the level of surplus and the external…

Optimization and Control · Mathematics 2015-06-30 Jinxia Zhu , Hailiang Yang

In this article, a notion of viscosity solutions is introduced for second order path-dependent Hamilton-Jacobi-Bellman (PHJB) equations associated with optimal control problems for path-dependent stochastic differential equations. We…

Optimization and Control · Mathematics 2022-12-26 Jianjun Zhou

We study an optimal control problem of McKean--Vlasov branching diffusion processes, in which the interaction term is determined by the marginal measure induced by all alive particles in the system. Accordingly, the value function is…

Optimization and Control · Mathematics 2025-12-02 Julien Claisse , Jiazhi Kang , Tianxu Lan , Xiaolu Tan

Stochastic optimal control problems have a long tradition in applied probability, with the questions addressed being of high relevance in a multitude of fields. Even though theoretical solutions are well understood in many scenarios, their…

Statistics Theory · Mathematics 2024-05-28 Sören Christensen , Claudia Strauch , Lukas Trottner

This paper is concerned with cost optimization of an insurance company. The surplus of the insurance company is modeled by a controlled regime switching diffusion, where the regime switching mechanism provides the fluctuations of the random…

Optimization and Control · Mathematics 2016-08-02 Chao Zhu

This paper, which is the natural continuation of a previous paper by the same authors, studies a class of optimal control problems with state constraints where the state equation is a differential equation with delays. This class includes…

Optimization and Control · Mathematics 2009-07-10 Salvatore Federico , Ben Goldys , Fausto Gozzi

This paper solves a Bayes sequential impulse control problem for a diffusion, whose drift has an unobservable parameter with a change point. The partially-observed problem is reformulated into one with full observations, via a change of…

Optimization and Control · Mathematics 2014-08-19 Lokman A. Abbas-Turki , Ioannis Karatzas , Qinghua Li

We characterize the optimal control for a class of singular stochastic control problems as the unique solution to a related Skorokhod reflection problem. The considered optimization problems concern the minimization of a discounted cost…

Optimization and Control · Mathematics 2023-05-22 Jodi Dianetti , Giorgio Ferrari

We study the optimal dividend problem for a firm's manager who has partial information on the profitability of the firm. The problem is formulated as one of singular stochastic control with partial information on the drift of the underlying…

Probability · Mathematics 2019-04-02 Tiziano De Angelis

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

Diffusion models have achieved remarkable success in generative modeling. Despite more stable training, the loss of diffusion models is not indicative of absolute data-fitting quality, since its optimal value is typically not zero but…

Machine Learning · Computer Science 2026-04-17 Yixian Xu , Shengjie Luo , Liwei Wang , Di He , Chang Liu
‹ Prev 1 3 4 5 6 7 10 Next ›