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We present novel results on the solution of a class of leavable, undiscounted optimal control problems in the minimax sense for nonlinear, continuous-state, discrete-time plants. The problem class includes entry-(exit-)time problems as well…

Optimization and Control · Mathematics 2018-09-05 Gunther Reissig , Matthias Rungger

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

We consider a large family of discrete and continuous time controlled Markov processes and study an ergodic risk-sensitive minimization problem. Under a blanket stability assumption, we provide a complete analysis to this problem. In…

Optimization and Control · Mathematics 2022-07-18 Anup Biswas , Somnath Pradhan

We study risk-sensitive control of continuous time Markov chains taking values in discrete state space. We study both finite and infinite horizon problems. In the finite horizon problem we characterise the value function via HJB equation…

Optimization and Control · Mathematics 2014-09-16 Mrinal K. Ghosh , Subhamay Saha

In this paper we study optimal stopping problems for nonlinear Markov processes driven by a McKean-Vlasov SDE and aim at solving them numerically by Monte Carlo. To this end we propose a novel regression algorithm based on the corresponding…

Numerical Analysis · Mathematics 2018-06-26 Denis Belomestny , John Schoenmakers

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

In this paper, we study the feasibility of a class of optimization-based boundary control of one-dimensional macroscopic traffic flow models, where stability and invariance are achieved by a single boundary control. We define the sets of…

Optimization and Control · Mathematics 2026-05-04 Eryn Vaid , Maria Teresa Chiri , Roberto Guglielmi , Gennaro Notomista

This paper analyzes the problem of starting and stopping a Cox-Ingersoll-Ross (CIR) process with fixed costs. In addition, we also study a related optimal switching problem that involves an infinite sequence of starts and stops. We…

Mathematical Finance · Quantitative Finance 2015-03-31 Tim Leung , Xin Li , Zheng Wang

This paper is devoted to studying constrained continuous-time Markov decision processes (MDPs) in the class of randomized policies depending on state histories. The transition rates may be unbounded, the reward and costs are admitted to be…

Probability · Mathematics 2012-01-04 Xianping Guo , Xinyuan Song

In this paper, we consider multistopping problems for finite discrete time sequences $X_1,...,X_n$. $m$-stops are allowed and the aim is to maximize the expected value of the best of these $m$ stops. The random variables are neither assumed…

Probability · Mathematics 2012-01-04 Andreas Faller , Ludger Rüschendorf

Filtration, flow in narrow channels and traffic flow are examples of processes subject to blocking when the channel conveying the particles becomes too crowded. If the blockage is temporary, which means that after a finite time the channel…

Statistical Mechanics · Physics 2018-08-01 G. Page , J. Resing , P. Viot , J. Talbot

This paper presents a new condition for the existence of optimal stationary policies in average-cost continuous-time Markov decision processes with unbounded cost and transition rates, arising from controlled queueing systems. This…

Optimization and Control · Mathematics 2015-04-23 Cao Ping , Xie Jingui

We consider optimal transport problems where the cost is optimized over controlled dynamics and the end time is free. Unlike the classical setting, the search for optimal transport plans also requires the identification of optimal "stopping…

Optimization and Control · Mathematics 2018-07-09 Nassif Ghoussoub , Young-Heon Kim , Aaron Zeff Palmer

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

In this paper we study a utility maximization problem with both optimal control and optimal stopping in a finite time horizon. The value function can be characterized by a variational equation that involves a free boundary problem of a…

Mathematical Finance · Quantitative Finance 2018-10-23 Jingtang Ma , Jie Xing , Harry Zheng

We study a Q learning algorithm for continuous time stochastic control problems. The proposed algorithm uses the sampled state process by discretizing the state and control action spaces under piece-wise constant control processes. We show…

Optimization and Control · Mathematics 2023-03-10 Erhan Bayraktar , Ali Devran Kara

In this paper, we prove the existence of classical solutions to second boundary value prob- lems for generated prescribed Jacobian equations, as recently developed by the second author, thereby obtaining extensions of classical solvability…

Analysis of PDEs · Mathematics 2018-02-14 Feida Jiang , Neil S. Trudinger

Given a spectrally negative L\'evy process, we predict, in a $L_1$ sense, the last passage time of the process below zero before an independent exponential time. This optimal prediction problem generalises Baurdoux and Pedraza (2020) where…

Probability · Mathematics 2021-08-11 Erik J. Baurdoux , José M. Pedraza

We study Markov processes where the "time" parameter is replaced by paths in a directed graph from an initial vertex to a terminal one. Along each directed path the process is Markov and has the same distribution as the one along any other…

Probability · Mathematics 2012-11-16 Krzysztof Burdzy , Soumik Pal

This paper studies the optimization of Markov decision processes (MDPs) from a risk-seeking perspective, where the risk is measured by conditional value-at-risk (CVaR). The objective is to find a policy that maximizes the long-run CVaR of…

Optimization and Control · Mathematics 2023-12-05 Li Xia , Zhihui Yu , Peter W. Glynn