Overview
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Table of contents (32 chapters)
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Stochastic Processes and Martingales
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Applications to Finance, Control Systems and Other Related Fields
About this book
The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South American and Asian scholars.
Editors and Affiliations
Bibliographic Information
Book Title: Markov Processes and Controlled Markov Chains
Editors: Zhenting Hou, Jerzy A. Filar, Anyue Chen
DOI: https://doi.org/10.1007/978-1-4613-0265-0
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Kluwer Academic Publishers 2002
Hardcover ISBN: 978-1-4020-0803-0Published: 30 September 2002
Softcover ISBN: 978-1-4613-7968-3Published: 17 September 2011
eBook ISBN: 978-1-4613-0265-0Published: 01 December 2013
Edition Number: 1
Number of Pages: X, 512
Topics: Probability Theory and Stochastic Processes, Operations Research/Decision Theory, Theoretical, Mathematical and Computational Physics, Mathematical and Computational Biology, Mathematical Modeling and Industrial Mathematics