Continuous-Time Markov Decision Processes: Theory and Applications (Stochastic Modelling and Applied Probability, 62)

Guo, Xianping; Hernández-Lerma, Onésimo

ISBN 10: 3642260721 / ISBN 13: 9783642260728

Published by Springer, 2012

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Seller Inventory # ABLIING23Mar3113020222051

Bibliographic Details

• Title: Continuous-Time Markov Decision Processes: Theory and Applications (Stochastic Modelling and Applied Probability, 62)
• Publisher: Springer
• Publication Date: 2012
• Language: English
• ISBN 10: 3642260721
• ISBN 13: 9783642260728
• Binding: Soft cover
• Condition: New

About this title

Synopsis

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.

About the Author

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.