This book is devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes. Interest is mainly confined to MCPs with Borel state and control spaces, and possibly unbounded costs. The book follows on from the authors earlier volume in this area, however, an important feature of the present volume is that it is essentially self-contained and can be read independently of the first volume, because although both volumes deal with similar classes of markov control processes the assumptions on the control models are usually different. This volume allows cost functions to take positive or negative values, as needed in some applications. The control model studied is sufficiently general to include virtually all the usual discrete-time stochastic control models that appear in applications to engineering, economics, mathematical population processes, operations research, and management science.
|Ergodicity and Poisson's Equation||p. 1|
|Discounted Dynamic Programming with Weighted Norms||p. 39|
|The Expected Total Cost Criterion||p. 75|
|Undiscounted Cost Criteria||p. 117|
|Sample Path Average Cost||p. 163|
|The Linear Programming Approach||p. 203|
|Glossary of notation||p. 265|
|Table of Contents provided by Blackwell. All Rights Reserved.|
Series: APPLICATIONS OF MATHEMATICS
Number Of Pages: 277
Published: 22nd June 1999
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 24.77 x 16.51 x 1.91
Weight (kg): 0.57