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We study reinforcement learning for controlled diffusion processes with unbounded continuous state spaces, bounded continuous actions, and polynomially growing rewards: settings that arise naturally in finance, economics, and operations…

Machine Learning · Computer Science 2025-12-18 Hanqing Jin , Renyuan Xu , Yanzhao Yang

We determine the variance-optimal hedge when the logarithm of the underlying price follows a process with stationary independent increments in discrete or continuous time. Although the general solution to this problem is known as backward…

Probability · Mathematics 2008-12-10 Friedrich Hubalek , Jan Kallsen , Leszek Krawczyk

In this paper, we study the consumption-chemotaxis-Stokes model with porous medium slow diffusion in a three dimensional bounded domain with zero-flux boundary conditions and no-slip boundary condition. In recent ten years, many efforts…

Analysis of PDEs · Mathematics 2021-01-28 Chunhua Jin

We adapt ideas and concepts developed in optimal transport (and its martingale variant) to give a geometric description of optimal stopping times of Brownian motion subject to the constraint that the distribution of the stopping time is a…

Probability · Mathematics 2017-09-14 Mathias Beiglboeck , Manu Eder , Christiane Elgert , Uwe Schmock

Many decision problems in economics, information technology, and industry can be transformed to an optimal stopping of adapted random vectors with some utility function over the set of Markov times with respect to filtration build by the…

Optimization and Control · Mathematics 2020-11-04 Krzysztof Szajowski

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

We consider an optimal control problem that entails the minimization of a nondifferentiable cost functional, fractional diffusion as state equation and constraints on the control variable. We provide existence, uniqueness and regularity…

Numerical Analysis · Mathematics 2017-04-05 Enrique Otárola , Abner J. Salgado

We propose a new method for solving optimal stopping problems (such as American option pricing in finance) under minimal assumptions on the underlying stochastic process $X$. We consider classic and randomized stopping times represented by…

Probability · Mathematics 2021-05-04 Christian Bayer , Paul Hager , Sebastian Riedel , John Schoenmakers

Recently, a series of papers proposed deep learning-based approaches to sample from target distributions using controlled diffusion processes, being trained only on the unnormalized target densities without access to samples. Building on…

Machine Learning · Computer Science 2024-05-24 Lorenz Richter , Julius Berner

We study the asymptotic diffusion processes with (generally nonlocal) open boundaries in one dimension which are exactly solvable by means of the recently developed recursion formula. We investigate the stationary states, which cannot be…

Statistical Mechanics · Physics 2007-05-23 Akira FUJII

In this paper, we study a sampling problem where a source takes samples from a Wiener process and transmits them through a wireless channel to a remote estimator. Due to channel fading, interference, and potential collisions, the packet…

Information Theory · Computer Science 2023-10-19 Jiayu Pan , Yin Sun , Ness B. Shroff

We analyze an optimal stopping problem with random maturity under a nonlinear expectation with respect to a weakly compact set of mutually singular probabilities $\mathcal{P}$. The maturity is specified as the hitting time to level $0$ of…

Probability · Mathematics 2016-07-08 Erhan Bayraktar , Song Yao

Fluid approximation is a widely used approach for solving two-stage stochastic optimization problems, with broad applications in service system design such as call centers and healthcare operations. However, replacing the underlying random…

Optimization and Control · Mathematics 2025-12-19 Can Er , Mo Liu

A finite horizon optimal stopping problem for an infinite dimensional diffusion $X$ is analyzed by means of variational techniques. The diffusion is driven by a SDE on a Hilbert space $\mathcal{H}$ with a non-linear diffusion coefficient…

Optimization and Control · Mathematics 2015-02-03 M. B. Chiarolla , T. De Angelis

The paper concerns the study and applications of a new class of optimal control problems governed by a perturbed sweeping process of the hysteresis type with control functions acting in both play-and-stop operator and additive…

Optimization and Control · Mathematics 2015-12-01 Tan H. Cao , Boris S. Mordukhovich

We consider the problem of stopping a diffusion process with a payoff functional that renders the problem time-inconsistent. We study stopping decisions of naive agents who reoptimize continuously in time, as well as equilibrium strategies…

Mathematical Finance · Quantitative Finance 2021-07-15 Yu-Jui Huang , Adrien Nguyen-Huu , Xun Yu Zhou

This paper considers a time-inconsistent stopping problem in which the inconsistency arises from non-constant time preference rates. We show that the smooth pasting principle, the main approach that has been used to construct explicit…

Mathematical Finance · Quantitative Finance 2019-09-05 Ken Seng Tan , Wei Wei , Xun Yu Zhou

In this paper, we consider optimal control problems derived by stochastic systems with delay, where control domains are non-convex and the diffusion coefficients depend on control variables. By an estimate of the integral of…

Optimization and Control · Mathematics 2022-10-25 Qixia Zhang

We consider a process given as the solution of a stochastic differential equation with irregular, path dependent and time-inhomogeneous drift coefficient and additive noise. Explicit and optimal bounds for the Lebesgue density of that…

Probability · Mathematics 2015-08-04 David Baños , Paul Krühner

We present a novel method for solving a class of time-inconsistent optimal stopping problems by reducing them to a family of standard stochastic optimal control problems. In particular, we convert an optimal stopping problem with a…

Optimization and Control · Mathematics 2016-11-15 Christopher W. Miller
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