Overview
- Provides a self-contained and easy-to-read introduction to dynamic programming
- Provides a comprehensive treatment of discrete-time multistage optimization
- Presents the theory of Markov decision processes without advanced measure theory
- Includes various examples and exercises (without solutions)
- Includes supplementary material: sn.pub/extras
Part of the book series: Universitext (UTX)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (26 chapters)
-
Deterministic Models
-
Markovian Decision Processes
Keywords
About this book
Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.
Reviews
Authors and Affiliations
About the authors
Ulrich Rieder is Professor emeritus at the University of Ulm. From 1990 to 2008, he was Editor-in-Chief of Mathematical Methods of Operations Research. His main research areas include stochastic dynamic programming and control, risk-sensitive Markov decision processes, stochastic games, and financial optimization.
Michael Stieglitz was Professor at the University of Karlsruhe until 2002. He contributes to summability, approximation theory, and probability.
Bibliographic Information
Book Title: Dynamic Optimization
Book Subtitle: Deterministic and Stochastic Models
Authors: Karl Hinderer, Ulrich Rieder, Michael Stieglitz
Series Title: Universitext
DOI: https://doi.org/10.1007/978-3-319-48814-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG 2016
Softcover ISBN: 978-3-319-48813-4Published: 18 January 2017
eBook ISBN: 978-3-319-48814-1Published: 12 January 2017
Series ISSN: 0172-5939
Series E-ISSN: 2191-6675
Edition Number: 1
Number of Pages: XXII, 530
Number of Illustrations: 22 b/w illustrations
Topics: Operations Research, Management Science, Systems Theory, Control, Discrete Optimization, Probability Theory and Stochastic Processes