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We study a class of multi-stage stochastic programs, which incorporate modeling features from Markov decision processes (MDPs). This class includes structured MDPs with continuous action and state spaces. We extend policy graphs to include…

Machine Learning · Computer Science 2026-04-09 David P. Morton , Oscar Dowson , Bernardo K. Pagnoncelli

In this paper we consider the problem of computing the stationary distribution of nearly completely decomposable Markov processes, a well-established area in the classical theory of Markov processes with broad applications in the design,…

Numerical Analysis · Mathematics 2025-06-19 Vasileios Kalantzis , Mark S. Squillante , Chai Wah Wu

Markov chains have long been used for generating random variates from spatial point processes. Broadly speaking, these chains fall into two categories: Metropolis-Hastings type chains running in discrete time and spatial birth-death chains…

Probability · Mathematics 2012-07-31 Mark Huber

This paper introduces several new classes of mathematical structures that have close connections with physics and with the theory of dynamical systems. The most general of these structures, called indivisible stochastic processes,…

Quantum Physics · Physics 2026-02-09 Jacob A. Barandes

Hybrid systems, and Piecewise Deterministic Markov Processes in particular, are widely used to model and numerically study systems exhibiting multiple time scales in biochemical reaction kinetics and related areas. In this paper an almost…

Numerical Analysis · Mathematics 2011-12-07 Martin G. Riedler

The main purpose of this paper is to consider the multiple birth properties for multi-type Markov branching processes. We first construct a new multi-dimensional Markov process based on the multi-type Markov branching process, which can…

Probability · Mathematics 2024-07-09 Junping Li , Wanting Zhang

We establish new conditions for obtaining uniform bounds on the moments of discrete-time stochastic processes. Our results require a weak negative drift criterion along with a state-dependent restriction on the sizes of the one-step jumps…

Probability · Mathematics 2022-06-02 Arnab Ganguly , Debasish Chatterjee

We consider a broad class of continuous-time two-type population size-dependent Markov Branching Processes. The offspring distribution can depend on the current (alive) and total (dead and alive) populations. Using stochastic approximation…

Probability · Mathematics 2023-04-04 Khushboo Agarwal , Veeraruna Kavitha

We consider an infinite locally finite system (configuration) $\gamma$ of particles distributed over a Euclidean space $X$. Each particle located at $x\in X$ carries an internal parameter (mark, or ``spin'') $\sigma_{x}\in S=\mathbb{R}.$…

Probability · Mathematics 2025-10-01 Alexei Daletskii , Dmitri Finkelshtein

We study a class of Markov processes with finite state space and continuous time that have product form stationary distributions. We obtain a number of examples that can generate conjectures for diffusions with inert drift.

Probability · Mathematics 2008-10-19 Krzysztof Burdzy , David White

Stochastic models that incorporate birth, death and immigration (also called birth-death and innovation models) are ubiquitous and applicable to many research topics such as quantifying species sizes in ecological populations, describing…

Populations and Evolution · Quantitative Biology 2026-05-12 Renaud Dessalles , Maria D'Orsogna , Tom Chou

This paper aims to provide a simple modelling of speculative bubbles and derive some quantitative properties of its dynamical evolution. Starting from a description of individual speculative behaviours, we build and study a second order…

Probability · Mathematics 2013-09-25 Sébastien Gadat , Laurent Miclo , Fabien Panloup

We investigate the large population dynamics of a family of stochastic particle systems with three-state cyclic individual behaviour and parameter-dependent transition rates. On short time scales, the dynamics turns out to be approximated…

Probability · Mathematics 2022-05-10 Julien Barré , Bastien Fernandez , Grégoire Panel

Many biological systems can be described by finite Markov models. A general method for simplifying master equations is presented that is based on merging adjacent states. The approach preserves the steady-state probability distribution and…

Biological Physics · Physics 2021-03-01 David Seiferth , Peter Sollich , Stefan Klumpp

Stochastic dynamics govern many important processes in cellular biology, and an underlying theoretical approach describing these dynamics is desirable to address a wealth of questions in biology and medicine. Mathematical tools exist for…

Quantitative Methods · Quantitative Biology 2016-02-17 Iain G. Johnston , Nick S. Jones

We consider a class of piecewise-deterministic Markov processes where the state evolves according to a linear dynamical system. This continuous time evolution is interspersed by discrete events that occur at random times and change (reset)…

Systems and Control · Computer Science 2017-11-15 Mohammad Soltani , Abhyudai Singh

In the recent article D\"oring et al. [4] the authors conditioned a stable process with two-sided jumps to avoid an interval. As usual the strategy was to find an invariant function for the process killed on entering the interval and to…

Probability · Mathematics 2020-02-19 Pierre Lenthe , Philip Weissmann

A new sufficient condition is proved for the existence of stochastic semigroups generated by the sum of two unbounded operators. It is applied to one-dimensional piecewise deterministic Markov processes, where we also discuss the existence…

Analysis of PDEs · Mathematics 2009-07-07 Michael C. Mackey , Marta Tyran-Kaminska

We give new formulas on the total number of born particles in the stable birth-and-assassination process, and prove that it has an heavy-tailed distribution. We also establish that this process is a scaling limit of a process of rumor…

Probability · Mathematics 2008-10-20 Charles Bordenave

In this note we consider a Markov chain formed by a finite system of interacting birth-and-death processes on a finite state space. We study an asymptotic behaviour of the Markov chain as its state space becomes large. In particular, we…

Probability · Mathematics 2016-11-14 Vadim Shcherbakov , Anatoly Yambartsev
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