Online Public Access Catalogue (OPAC)
Library,Documentation and Information Science Division

“A research journal serves that narrow

borderland which separates the known from the unknown”

-P.C.Mahalanobis


Image from Google Jackets

Continuous-Time Markov Decision Processes [electronic resource] : Theory and Applications / by Xianping Guo, Onésimo Hernández-Lerma.

By: Contributor(s): Material type: TextTextSeries: Stochastic Modelling and Applied Probability ; 62Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Description: XVIII, 234 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642025471
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519.6 23
LOC classification:
  • QA402.5-402.6
Online resources:
Contents:
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.
In: Springer eBooksSummary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

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.

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.

There are no comments on this title.

to post a comment.
Library, Documentation and Information Science Division, Indian Statistical Institute, 203 B T Road, Kolkata 700108, INDIA
Phone no. 91-33-2575 2100, Fax no. 91-33-2578 1412, ksatpathy@isical.ac.in