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Simulation-Based Algorithms for Markov Decision Processes (Record no. 10538)

000 -LEADER
fixed length control field 04135nam a22005295i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310143335.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130228s2013 xxk| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781447150220
978-1-4471-5022-0
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 629.8
Edition number 23
264 #1 -
-- London :
-- Springer London :
-- Imprint: Springer,
-- 2013.
912 ## -
-- ZDB-2-ENG
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Chang, Hyeong Soo.
Relator term author.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Simulation-Based Algorithms for Markov Decision Processes
Medium [electronic resource] /
Statement of responsibility, etc by Hyeong Soo Chang, Jiaqiao Hu, Michael C. Fu, Steven I. Marcus.
250 ## - EDITION STATEMENT
Edition statement 2nd ed. 2013.
300 ## - PHYSICAL DESCRIPTION
Extent XVII, 229 p. 29 illus., 1 illus. in color.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Communications and Control Engineering,
International Standard Serial Number 0178-5354
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Markov Decision Processes -- Multi-stage Adaptive Sampling Algorithms -- Population-based Evolutionary Approaches -- Model Reference Adaptive Search -- On-line Control Methods via Simulation -- Game-theoretic Methods via Simulation.
520 ## - SUMMARY, ETC.
Summary, etc Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.  Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical solution of the resulting models intractable.  In other cases, the system of interest is too complex to allow explicit specification of some of the MDP model parameters, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based algorithms have been developed to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function.  Specific approaches include adaptive sampling, evolutionary policy iteration, evolutionary random policy search, and model reference adaptive search. This substantially enlarged new edition reflects the latest developments in novel algorithms and their underpinning theories, and presents an updated account of the topics that have emerged since the publication of the first edition. Includes: . innovative material on MDPs, both in constrained settings and with uncertain transition properties; . game-theoretic method for solving MDPs; . theories for developing roll-out based algorithms; and . details of approximation stochastic annealing, a population-based on-line simulation-based algorithm. The self-contained approach of this book will appeal not only to researchers in MDPs, stochastic modeling, and control, and simulation but will be a valuable source of tuition and reference for students of control and operations research. The Communications and Control Engineering series reports major technological advances which have potential for great impact in the fields of communication and control. It reflects research in industrial and academic institutions around the world so that the readership can exploit new possibilities as they become available.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
Topical term or geographic name as entry element Computer software.
Topical term or geographic name as entry element Systems theory.
Topical term or geographic name as entry element Distribution (Probability theory).
Topical term or geographic name as entry element Operations research.
Topical term or geographic name as entry element Engineering.
Topical term or geographic name as entry element Control.
Topical term or geographic name as entry element Systems Theory, Control.
Topical term or geographic name as entry element Probability Theory and Stochastic Processes.
Topical term or geographic name as entry element Operations Research, Management Science.
Topical term or geographic name as entry element Algorithm Analysis and Problem Complexity.
Topical term or geographic name as entry element Operation Research/Decision Theory.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hu, Jiaqiao.
Relator term author.
Personal name Fu, Michael C.
Relator term author.
Personal name Marcus, Steven I.
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781447150213
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4471-5022-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-03-29AUM Main Library2014-03-29 2014-03-29 E-Book   AUM Main Library629.8

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