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We adopt an optimal-control framework for addressing the undiscounted infinite-horizon discrete-time restless $N$-armed bandit problem. Unlike most studies that rely on constructing policies based on the relaxed single-armed Markov Decision…

Optimization and Control · Mathematics 2024-03-19 Chen YAN

In a classical optimal stopping problem in continuous time, the agent can choose any stopping time without constraint. Dupuis and Wang (Optimal stopping with random intervention times, Advances in Applied Probability, 34, 141--157, 2002)…

Probability · Mathematics 2019-01-23 David Hobson , Matthew Zeng

A new class of Hermite methods for solving nonlinear conservation laws is presented. While preserving the high order spatial accuracy for smooth solutions in the existing Hermite methods, the new methods come with better stability…

Numerical Analysis · Mathematics 2017-03-21 Adeline Kornelus , Daniel Appelö

We consider a class of exit time stochastic control problems for diffusion processes with discounted criterion, where the controller can utilize a given amount of resource, called "fuel". In contrast to the vast majority of existing…

Optimization and Control · Mathematics 2015-01-30 Dmitry B. Rokhlin , Georgii Mironenko

In this paper, we describe a novel approach for checking safety specifications of a dynamical system with exogenous inputs over infinite time horizon that is guaranteed to terminate in finite time with a conclusive answer. We introduce the…

Optimization and Control · Mathematics 2008-01-04 Amit Bhatia , Emilio Frazzoli

The paper proposes a scheme by combining the Runge-Kutta discontinuous Galerkin method with a {\delta}-mapping algorithm for solving hyperbolic conservation laws with discontinuous fluxes. This hybrid scheme is particularly applied to…

Numerical Analysis · Mathematics 2015-11-05 Dian-liang Qiao , Peng Zhang , Zhi-yang Lin , S. C. Wong , Keechoo Choi

In optimal stopping problems, a Markov structure guarantees Markovian optimal stopping times (first exit times). Surprisingly, there is no analogous result for Markovian stopping games once randomization is required. This paper addresses…

Probability · Mathematics 2024-08-02 Sören Christensen , Boy Schultz

In this paper, we propose a new hybridized discontinuous Galerkin (DG) method for the convection-diffusion problems with mixed boundary conditions. A feature of the proposed method, is that it can greatly reduce the number of…

Numerical Analysis · Mathematics 2013-11-01 Issei Oikawa

This paper studies the stochastic optimal control of jump-diffusion processes and the associated fully nonlinear backward stochastic Hamilton--Jacobi--Bellman (BSHJB) equations. We establish the dynamic programming principle (DPP) via…

Optimization and Control · Mathematics 2026-05-21 Dunxiang Liang , Qingxin Meng

Wormhole propagation plays a very important role in the product enhancement of oil and gas reservoir. A new combined hybrid mixed finite element method is proposed to solve incompressible wormhole propagation problem with discontinuous…

Numerical Analysis · Mathematics 2022-09-07 Jiansong Zhang , Yun Yu , Jiang Zhu , Yue Yu , Rong Qin

We address on general quantum-statistical grounds the problem of optimal detection of the Unruh-Hawking effect. We show that the effect signatures are magnified up to potentially observable levels if the scalar field to be probed has high…

Quantum Physics · Physics 2010-10-27 Mariona Aspachs , Gerardo Adesso , Ivette Fuentes

In this paper, we develop new optional stopping theorems for scenarios where the stopping rules are defined by bounded continuity regions. Moreover, we establish a wide variety of inequalities on the supremums and infimums of functions of…

Probability · Mathematics 2012-08-01 Xinjia Chen

In this paper we study the optimal stopping problem for L\'evy processes studied by Novikov and Shiryayev, Stochastics, 2007 In particular, we are interested in finding the representing measure of the value function. It is seen that that…

Probability · Mathematics 2010-02-22 Paavo Salminen

The problem of optimal stopping with finite horizon in discrete time is considered in view of maximizing the expected gain. The algorithm proposed in this paper is completely nonparametric in the sense that it uses observed data from the…

Statistics Theory · Mathematics 2013-07-24 Michael Kohler , Harro Walk

Many discrete-time optimal stopping problems are known to have more tractable limit forms based on a planar Poisson process. Using this tool we find a solution to the optimal stopping problem for i.i.d. sequence of $n$ discrete uniform…

Probability · Mathematics 2026-01-09 Alexander Gnedin

In this paper, a new stabilized discontinuous Galerkin method within a new function space setting is introduced, which involves an extra stabilization term on the normal fluxes across the element interfaces. It is different from the general…

Numerical Analysis · Mathematics 2014-11-25 Zhihao Ge , Jiwei Cao

We present a novel discontinuous Galerkin algorithm for the solution of a class of Fokker-Planck collision operators. These operators arise in many fields of physics, and our particular application is for kinetic plasma simulations. In…

Computational Physics · Physics 2020-08-26 Ammar Hakim , M. Francisquez , J. Juno , Greg W. Hammett

In this paper, we extend the jump-diffusion model proposed by Davis and Lleo to include jumps in asset prices as well as valuation factors. The criterion, following earlier work by Bielecki, Pliska, Nagai and others, is risk-sensitive…

Portfolio Management · Quantitative Finance 2010-03-15 Mark Davis , Sebastien Lleo

In this paper, we propose to apply the parametrized maximum-principle-preserving (MPP) flux limiter in [Xiong et. al., JCP, 2013] to the discontinuous Galerkin (DG) method for solving the convection-diffusion equations. The feasibility of…

Numerical Analysis · Mathematics 2014-04-17 Tao Xiong , Jingmei Qiu , Zhengfu Xu

In this work, we propose a novel machine learning approach to compute the optimal transport map between two continuous distributions from their unpaired samples, based on the DeepParticle methods. The proposed method leads to a min-min…

Machine Learning · Statistics 2025-07-01 Yingyuan Li , Aokun Wang , Zhongjian Wang
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