Markov Processes and Controlled Markov Chains

Zhenting Hou

ISBN 10: 1461379687 / ISBN 13: 9781461379683

Published by Springer US, 2011

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9781461379683

Bibliographic Details

• Title: Markov Processes and Controlled Markov Chains
• Publisher: Springer US
• Publication Date: 2011
• Language: English
• ISBN 10: 1461379687
• ISBN 13: 9781461379683
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 240W x 160H x 29D millimeters 240 millimeters width by 160 millimeters height by 29 millimeters depth
• Weight: 828 grams

About this title

Synopsis

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.