Dynamic Optimization
Springer International Publishing (Verlag)
978-3-319-48813-4 (ISBN)
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.
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.
Introduction and Organization of the Book.- Part I Deterministic Models.- Part II Markovian Decision Processes.- Part III Generalizations of Markovian Decision Processes.- Part IV Appendix.
"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)
“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)
| Erscheinungsdatum | 29.01.2017 |
|---|---|
| Reihe/Serie | Universitext |
| Zusatzinfo | XXII, 530 p. 22 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Mathematik |
| Wirtschaft ► Betriebswirtschaft / Management | |
| Schlagworte | Bayesian control models • Cybernetics and systems theory • Discrete Optimization • discrete-time multi-stage optimization • Dynamic Programming • Management and management techniques • Markov Decision Processes • Markov renewal programs • Mathematics • mathematics and statistics • Networks • Operational Research • Operations Research, Management Science • Optimization • partially observable processes • probability and statistics • Probability theory and stochastic processes • Stochastic Optimal Control • stochastics • Systems Theory, Control |
| ISBN-10 | 3-319-48813-9 / 3319488139 |
| ISBN-13 | 978-3-319-48813-4 / 9783319488134 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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