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Universitext

Dynamic Optimization

Deterministic and Stochastic Models

Authors: Hinderer, Karl, Rieder, Ulrich, Stieglitz, Michael

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  • 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)
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  • ISBN 978-3-319-48814-1
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About this Textbook

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance.
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.

About the authors

Karl Hinderer was Professor of Stochastics at the Karlsruhe Institute of Technology KIT. He wrote the seminal book Foundations of Non-stationary Dynamic Programming with Discrete Time Parameter (1970) and the textbook Grundbegriffe der Wahrscheinlichkeitstheorie (1972). His main research areas were stochastic dynamic programming, probability and stochastic processes.
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.

Reviews

“Part I deals with deterministic dynamic optimization models describing the control of discrete-time systems. Part II is devoted to discrete-time stochastic control models. Part III … is devoted to Markovian decision processes with disturbances… The book comprises a lot of examples, problems for readers, and supplements with additional comments for the advanced reader and with bibliographic notes.” (Svetlana A. Kravchenko, zbMATH 1365.90002)

Table of contents (26 chapters)

Table of contents (26 chapters)

Buy this book

eBook $84.99
price for USA in USD (gross)
  • ISBN 978-3-319-48814-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $109.99
price for USA in USD
  • ISBN 978-3-319-48813-4
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Dynamic Optimization
Book Subtitle
Deterministic and Stochastic Models
Authors
Series Title
Universitext
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-48814-1
DOI
10.1007/978-3-319-48814-1
Softcover ISBN
978-3-319-48813-4
Series ISSN
0172-5939
Edition Number
1
Number of Pages
XXII, 530
Number of Illustrations
22 b/w illustrations
Topics

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