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This paper describes the structure of solutions to Kolmogorov's equations for nonhomogeneous jump Markov processes and applications of these results to control of jump stochastic systems. These equations were studied by Feller (1940), who…

Probability · Mathematics 2021-11-09 Eugene A. Feinberg , Albert N. Shiryaev

Markov decision processes (MDPs) in queues and networks have been an interesting topic in many practical areas since the 1960s. This paper provides a detailed overview on this topic and tracks the evolution of many basic results. Also, this…

Optimization and Control · Mathematics 2019-08-26 Quan-Lin Li , Jing-Yu Ma , Rui-Na Fan , Li Xia

This document is an internet supplement to my book "Partially Observed Markov Decision Processes - From Filtering to Controlled Sensing" published by Cambridge University Press in 2016. This internet supplement contains exercises, examples…

Optimization and Control · Mathematics 2016-04-28 Vikram Krishnamurthy

This paper deals with control of partially observable discrete-time stochastic systems. It introduces and studies Markov Decision Processes with Incomplete Information and with semi-uniform Feller transition probabilities. The important…

Optimization and Control · Mathematics 2022-08-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

This paper considers the optimal control of time varying continuous time Markov chains whose transition rates are themselves Markov processes. In one set of problems the solution of an ordinary differential equation is shown to determine…

Systems and Control · Computer Science 2015-09-02 Manish Gupta

We study optimal control of Markov processes with age-dependent transition rates. The control policy is chosen continuously over time based on the state of the process and its age. We study infinite horizon discounted cost and infinite…

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

The program of studying general nonlinear Markov processes was put forward in V. N. Kolokoltsov "Nonlinear Markov Semigroups and Interacting L\'evy Type Processes" (Journ. Stat. Physics 126:3 (2007), 585-642), and was developed by the…

Probability · Mathematics 2022-05-03 Vassili N. Kolokoltsov

We give a short overview of recent results on a specific class of Markov process: the Piecewise Deterministic Markov Processes (PDMPs). We first recall the definition of these processes and give some general results. On more specific cases…

Statistics Theory · Mathematics 2013-09-25 Romain Azaïs , Jean-Baptiste Bardet , Alexandre Genadot , Nathalie Krell , Pierre-André Zitt

This note summarizes the optimization formulations used in the study of Markov decision processes. We consider both the discounted and undiscounted processes under the standard and the entropy-regularized settings. For each setting, we…

Optimization and Control · Mathematics 2020-12-18 Lexing Ying , Yuhua Zhu

This paper studies: (i) the long time behaviour of the empirical distribution of age and normalised position of an age dependent critical branching Markov process conditioned on non-extinction; and (ii) the super-process limit of a sequence…

Probability · Mathematics 2007-05-23 Krishna Athreya , Siva Athreya , Srikanth Iyer

In this paper, we study a continuous-time discounted jump Markov decision process with both controlled actions and observations. The observation is only available for a discrete set of time instances. At each time of observation, one has to…

Optimization and Control · Mathematics 2019-07-16 Yunhan Huang , Veeraruna Kavitha , Quanyan Zhu

Markov jump processes are widely used to model natural and engineered processes. In the context of biological or chemical applications one typically refers to the chemical master equation (CME), which models the evolution of the probability…

Optimization and Control · Mathematics 2017-07-05 Wei Zhang , Carsten Hartmann , Max von Kleist

Motivated by entropic optimal transport, time reversal of Markov jump processes in $\mathbb{R}^n$ is investigated. Relying on an abstract integration by parts formula for the carr\'e du champ of a Markov process recently obtained by…

Probability · Mathematics 2022-09-05 Giovanni Conforti , Christian Léonard

This is lecture notes on the course "Stochastic Processes". In this format, the course was taught in the spring semesters 2017 and 2018 for third-year bachelor students of the Department of Control and Applied Mathematics, School of Applied…

Markov jump processes are continuous-time stochastic processes with a wide range of applications in both natural and social sciences. Despite their widespread use, inference in these models is highly non-trivial and typically proceeds via…

Machine Learning · Computer Science 2023-06-01 Patrick Seifner , Ramses J. Sanchez

Markov Decision Processes (MDPs) have been used to formulate many decision-making problems in science and engineering. The objective is to synthesize the best decision (action selection) policies to maximize expected rewards (or minimize…

Optimization and Control · Mathematics 2015-07-07 Mahmoud El Chamie , Behcet Acikmese

This is the first part of a possible monograph on the duality of Markov processes. It contains a proof of Fitzsimmons' existence theorem of a moderate Markov dual process relative to an excessive measure, m, together with the necessary…

Probability · Mathematics 2010-02-12 Ronald Getoor

The goal of this paper is threefold. First, we survey the existing results on Hunt's hypothesis (H) for Markov processes and Getoor's conjecture for L\'{e}vy processes. Second, we investigate (H) for multidimensional L\'{e}vy processes from…

Probability · Mathematics 2019-08-20 Ze-Chun Hu , Wei Sun

Control theory plays a pivotal role in understanding and optimizing the behavior of complex dynamical systems across various scientific and engineering disciplines. Two key frameworks that have emerged for modeling and solving control…

Methodology · Statistics 2025-04-15 Alice Cleynen , Benoîte de Saporta , Orlane Rossini , Régis Sabbadin , Amélie Vernay

In the paper we study continuous time controlled Markov processes using discrete time controlled Markov processes. We consider long run functionals: average reward per unit time or long run risk sensitive functional. We also investigate…

Optimization and Control · Mathematics 2025-08-12 Lukasz Stettner
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