Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. <br>The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequ
Introduction to Dynamic Programming
โ Scribed by Leon Cooper, Mary W. Cooper and E. Y. Rodin (Auth.)
- Publisher
- Elsevier Ltd, Pergamon Press
- Year
- 1981
- Tongue
- English
- Leaves
- 292
- Series
- Pergamon International Library of Science, Technology, Engineering & Social Studies
- Edition
- 1st
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Content:
International Series in MODERN APPLIED MATHEMAWCS AND COMPUTER SCIENCE, Page ii
Front Matter, Page iii
Copyright, Page iv
Preface, Page v
Chapter 1 - Introduction, Pages 1-12
Chapter 2 - Some Simple Examples, Pages 13-30
Chapter 3 - Functional Equations: Basic Theory, Pages 31-44
Chapter 4 - One-dimensional Dynamic Programming: Analytic Solutions, Pages 45-85
Chapter 5 - One-dimensional Dynamic Programming: Computational Solutions, Pages 86-126
Chapter 6 - Multidimensional Problems, Pages 127-154
Chapter 7 - Reduction of State Dimensionality and Approximations, Pages 155-188
Chapter 8 - Stochastic Processes and Dynamic Programming, Pages 189-216
Chapter 9 - Dynamic Programming and the Calculus of Variations, Pages 217-250
Chapter 10 - Applications of Dynamic Programming, Pages 251-277
Appendix - Sets, Convexity, and n-Dimensional Geometry, Pages 279-286
References, Pages 287-288
Index, Page 289
๐ SIMILAR VOLUMES
<p><span>This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management
<p><span>This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management
This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management Science,