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We study the problem of characterizing the expected hitting times for a robust generalization of continuous-time Markov chains. This generalization is based on the theory of imprecise probabilities, and the models with which we work…

Probability · Mathematics 2022-06-28 Thomas Krak

In the present paper, we investigate the relationship between hitting times and hitting probabilities in discrete-time imprecise Markov chains (IMCs). We define lower and upper hitting times and probabilities for IMCs whose set of…

Probability · Mathematics 2026-03-18 Marco Sangalli , Erik Quaeghebeur , Thomas Krak

We study the computation of lower and upper probabilities of hitting a target set of states for imprecise Markov chains, where transition uncertainty is modelled by a convex set of transition matrices. In the precise case, hitting…

Probability · Mathematics 2026-03-18 Marco Sangalli , Erik Quaeghebeur , Thomas Krak

Imprecise continuous-time Markov chains are a robust type of continuous-time Markov chains that allow for partially specified time-dependent parameters. Computing inferences for them requires the solution of a non-linear differential…

Probability · Mathematics 2018-10-11 Alexander Erreygers , Jasper De Bock

In this paper, we extend hitting times for imprecise Markov chains to the framework of weighted imprecise Markov chains (WIMCs), in which each transition is associated with a strictly positive weight encoded by a matrix $W$. Given a convex…

Probability · Mathematics 2026-03-18 Marco Sangalli , Thomas Krak

We present a novel algorithm to solve a non-linear system of equations, whose solution can be interpreted as a tight lower bound on the vector of expected hitting times of a Markov chain whose transition probabilities are only partially…

Probability · Mathematics 2022-03-30 Thomas Krak

We present an algorithm that can efficiently compute a broad class of inferences for discrete-time imprecise Markov chains, a generalised type of Markov chains that allows one to take into account partially specified probabilities and other…

Probability · Mathematics 2019-07-02 Natan T'Joens , Thomas Krak , Jasper De Bock , Gert de Cooman

When the initial and transition probabilities of a finite Markov chain in discrete time are not well known, we should perform a sensitivity analysis. This can be done by considering as basic uncertainty models the so-called credal sets that…

Probability · Mathematics 2009-11-24 Gert de Cooman , Filip Hermans , Erik Quaeghebeur

We justify and discuss expressions for joint lower and upper expectations in imprecise probability trees, in terms of the sub- and supermartingales that can be associated with such trees. These imprecise probability trees can be seen as…

Probability · Mathematics 2016-01-19 Gert de Cooman , Jasper De Bock , Stavros Lopatatzidis

We consider the problem of performing inference with imprecise continuous-time hidden Markov chains, that is, imprecise continuous-time Markov chains that are augmented with random output variables whose distribution depends on the hidden…

Probability · Mathematics 2017-05-09 Thomas Krak , Jasper De Bock , Arno Siebes

When the initial and transition probabilities of a finite Markov chain in discrete time are not well known, we should perform a sensitivity analysis. This is done by considering as basic uncertainty models the so-called credal sets that…

Artificial Intelligence · Computer Science 2014-08-12 Gert de Cooman , Filip Hermans , Erik Quaeghebeur

Motivated by applications in telecommunications, computer scienceand physics, we consider a discrete-time Markov process withrestart. At each step the process eitherwith a positive probability restarts from a given distribution, orwith the…

Performance · Computer Science 2017-03-13 Konstantin Avrachenkov , Alexey Piunovskiy , Yi Zhang

The convergence, convergence rate and expected hitting time play fundamental roles in the analysis of randomised search heuristics. This paper presents a unified Markov chain approach to studying them. Using the approach, the sufficient and…

Optimization and Control · Mathematics 2013-12-10 Jun He , Feidun He , Xin Yao

Continuous-time Markov chains are mathematical models that are used to describe the state-evolution of dynamical systems under stochastic uncertainty, and have found widespread applications in various fields. In order to make these models…

Probability · Mathematics 2017-06-22 Thomas Krak , Jasper De Bock , Arno Siebes

Given an irreducible discrete-time Markov chain on a finite state space, we consider the largest expected hitting time $T(\alpha)$ of a set of stationary measure at least $\alpha$ for $\alpha\in(0,1)$. We obtain tight inequalities among the…

Probability · Mathematics 2015-10-29 Simon Griffiths , Ross J. Kang , Roberto Imbuzeiro Oliveira , Viresh Patel

We analyse the structure of imprecise Markov chains and study their convergence by means of accessibility relations. We first identify the sets of states, so-called minimal permanent classes, that are the minimal sets capable of containing…

Probability · Mathematics 2016-09-20 Damjan Skulj

If the state space of a homogeneous continuous-time Markov chain is too large, making inferences - here limited to determining marginal or limit expectations - becomes computationally infeasible. Fortunately, the state space of such a chain…

Probability · Mathematics 2018-06-01 Alexander Erreygers , Jasper De Bock

The effect of perturbations of parameters for uniquely convergent imprecise Markov chains is studied. We provide the maximal distance between the distributions of original and perturbed chain and maximal degree of imprecision, given the…

Probability · Mathematics 2022-09-29 Damjan Škulj

In this paper we are concerned with hitting times of a family of density-dependent Markov chains. A moderate deviation principle of the hitting time is given. The proof of the main theorem relies heavily on moderate deviations of…

Probability · Mathematics 2022-06-15 Yuheng He , Xiaofeng Xue

In this work, we consider an inhomogeneous (discrete time) Markov chain and are interested in its long time behavior. We provide sufficient conditions to ensure that some of its asymptotic properties can be related to the ones of a…

Probability · Mathematics 2017-11-09 Michel Benaïm , Florian Bouguet , Bertrand Cloez
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