Del 62 - Stochastic Modelling and Applied Probability

Continuous-Time Markov Decision Processes

Theory and Applications

Häftad, Engelska, 2012

Av Xianping Guo, Onésimo Hernández-Lerma

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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.

Produktinformation

Utgivningsdatum2012-03-14
Mått155 x 235 x 14 mm
Vikt388 g
FormatHäftad
SpråkEngelska
SerieStochastic Modelling and Applied Probability
Antal sidor234
Upplaga2009
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783642260728

Tillhör följande kategorier

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.

From the reviews:“The book consists of 12 chapters. … this is the first monograph on continuous-time Markov decision process. … This is an important book written by leading experts on a mathematically rich topic which has many applications to engineering, business, and biological problems. … scholars and students interested in developing the theory of continuous-time Markov decision Processes or working on their applications should have this book.” (E. A. Feinberg, Mathematical Reviews, Issue 2011 b)