Guo / Hernández-Lerma / Hernandez-Lerma Continuous-Time Markov Decision Processes

Theory and Applications
1. Auflage 2009
ISBN: 978-3-642-02547-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 62, 234 Seiten, eBook

Reihe: Stochastic Modelling and Applied Probability

Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer science, communications engineering, control of populations (such as fisheries and epidemics), and management science, among many other fields. This volume provides a unified, systematic, self-contained presentation of recent developments on the theory and applications of continuous-time MDPs. The MDPs in this volume include most of the cases that arise in applications, because they allow unbounded transition and reward/cost rates. Much of the material appears for the first time in book form.

Zielgruppe

Research

Autoren/Hrsg.

Guo, Xianping

Hernández-Lerma, Onésimo

Hernandez-Lerma, Onesimo

Inhaltsverzeichnis

and Summary.- Continuous-Time Markov Decision Processes.- Average Optimality for Finite Models.- Discount Optimality for Nonnegative Costs.- Average Optimality for Nonnegative Costs.- Discount Optimality for Unbounded Rewards.- Average Optimality for Unbounded Rewards.- Average Optimality for Pathwise Rewards.- Advanced Optimality Criteria.- Variance Minimization.- Constrained Optimality for Discount Criteria.- Constrained Optimality for Average Criteria.

Über Autor(innen)

Onésimo Hernández-Lerma received the Science and Arts National Award from the Government of MEXICO in 2001, an honorary doctorate from the University of Sonora in 2003, and the Scopus Prize from Elsevier in 2008. Xianping Guo received the He-Pan-Qing-Yi Best Paper Award from the 7th Word Congress on Intelligent Control and Automation in 2008.