Examples in Markov decision processes
 Responsibility
 A.B. Piunovskiy.
 Language
 English.
 Imprint
 London : Imperial College Press, c2013.
 Physical description
 xiii, 293 p. : ill. ; 24 cm.
 Series
 Imperial College Press optimization series ; v. 2.
Access
Available online
Math & Statistics Library
Stacks
Call number  Status 

QA274.7 .P58 2013  Unknown 
More options
Creators/Contributors
 Author/Creator
 Piunovskiy, A. B.
Contents/Summary
 Bibliography
 Includes bibliographical references (p. 285290) and index.
 Contents

 Finite Horizon Models Infinite Horizon Models, Expected Total Loss and Discounted Loss Long Run Average Loss.
 (source: Nielsen Book Data)
 Publisher's Summary
 This invaluable book provides approximately eighty examples illustrating the theory of controlled discretetime Markov processes. Except for applications of the theory to reallife problems like stock exchange, queues, gambling, optimal search etc, the main attention is paid to counterintuitive, unexpected properties of optimization problems. Such examples illustrate the importance of conditions imposed in the theorems on Markov Decision Processes. Many of the examples are based upon examples published earlier in journal articles or textbooks while several other examples are new. The aim was to collect them together in one reference book which should be considered as a complement to existing monographs on Markov decision processes. This book is selfcontained and unified in presentation. The main theoretical statements and constructions are provided, and particular examples can be read independently of others. "Examples in Markov Decision Processes" is an essential source of reference for mathematicians and all those who apply the optimal control theory to practical purposes. When studying or using mathematical methods, the researcher must understand what can happen if some of the conditions imposed in rigorous theorems are not satisfied. Many examples confirming the importance of such conditions were published in different journal articles which are often difficult to find. This book brings together examples based upon such sources, along with several new ones. In addition, it indicates the areas where Markov decision processes can be used. Active researchers can refer to this book on applicability of mathematical methods and theorems. It is also suitable reading for graduate and research students where they will better understand the theory.
(source: Nielsen Book Data)
Subjects
 Subject
 Markov processes.
Bibliographic information
 Publication date
 2013
 Series
 Imperial College Press optimization series, 20411677 ; v. 2
 ISBN
 9781848167933 (hbk.)
 1848167938 (hbk.)