Introduction to Stochastic Dynamic Programming - 1st Edition - ISBN: 9780125984201, 9781483269092

Introduction to Stochastic Dynamic Programming

1st Edition

Authors: Sheldon Ross
Editors: Z. W. Birnbaum E. Lukacs
eBook ISBN: 9781483269092
Imprint: Academic Press
Published Date: 28th March 1983
Page Count: 178
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Description

Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming.
The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist—providing counterexamples where appropriate—and then presents methods for obtaining such policies when they do. In addition, general areas of application are presented.
The final two chapters are concerned with more specialized models. These include stochastic scheduling models and a type of process known as a multiproject bandit. The mathematical prerequisites for this text are relatively few. No prior knowledge of dynamic programming is assumed and only a moderate familiarity with probability— including the use of conditional expectation—is necessary.

Table of Contents


Preface

I. Finite-Stage Models

1. Introduction

2. A Gambling Model

3. A Stock-Option Model

4. Modular Functions and Monotone Policies

5. Accepting the Best Offer

6. A Sequential Allocation Model

7. The Interchange Argument in Sequencing

Problems

Notes and References

II. Discounted Dynamic Programming

1. Introduction

2. The Optimality Equation and Optimal Policy

3. Method of Successive Approximations

4. Policy Improvement

5. Solution by Linear Programming

6. Extension to Unbounded Rewards

Problems

References

III. Minimizing Costs—Negative Dynamic Programming

1. Introduction and Some Theoretical Results

2. Optimal Stopping Problems

3. Bayesian Sequential Analysis

4. Computational Approaches

5. Optimal Search

Problems

References

IV. Maximizing Rewards—Positive Dynamic Programming

1. Introduction and Main Theoretical Results

2. Applications to Gambling Theory

3. Computational Approaches to Obtaining V

Problems

Notes and References

V. Average Reward Criterion

1. Introduction and Counterexamples

2. Existence of an Optimal Stationary Policy

3. Computational Approaches

Problems

Notes and References

VI. Stochastic Scheduling

1. Introduction

2. Maximizing Finite-Time Returns—Single Processor

3. Minimizing Expected Makespan—Processors in Parallel

4. Minimizing Expected Makespan—Processors in Series

5. Maximizing Total Field Life

6. A Stochastic Knapsack Model

7. A Sequential-Assignment Problem

Problems

Notes and References

VII. Bandit Processes

1. Introduction

2. Single-Project Bandit Processes

3. Multiproject Bandit Processes

4. An Extension and a Nonextension

5. Generalizations of the Classical Bandit Problem

Problems

Notes and References

Appendix: Stochastic Order Relations

1. Stochastically Larger

2. Coupling

3. Hazard-Rate Ordering

4. Likelihood-Ratio Ordering

Problems

Reference

Index

Details

No. of pages:
178
Language:
English
Copyright:
© Academic Press 1983
Published:
Imprint:
Academic Press
eBook ISBN:
9781483269092

About the Author

Sheldon Ross

Sheldon Ross

Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.

Affiliations and Expertise

University of Southern California, Los Angeles, USA

About the Editor

Z. W. Birnbaum

E. Lukacs

Affiliations and Expertise

Bowling Green State University

Ratings and Reviews