Decision Theory: An Introduction to Dynamic Programming and Sequential Decisions / Edition 1

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Overview

Opening with a brief discussion of the historical background, the book describes deterministic models, in which the choice between decision is unaffected by chance. Then considering decision in the face of uncertainty, the material then closes with a discussion of more complex models, introduction the reader to a wide range of applications of the method.
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Editorial Reviews

Short Book Reviews
This textbook...draws on his many years of experience in teaching this topic as well as on his considerable professional expertise in the area. It is ideally suited to its stated purpose as a student text.
Short Book Reviews
This textbook...draws on his many years of experience in teaching this topic as well as on his considerable professional expertise in the area. It is ideally suited to its stated purpose as a student text.
From the Publisher
"This textbook...draws on his many years of experience in teaching this topic as well as on his considerable professional expertise in the area. It is ideally suited to its stated purpose as a student text." (Short Book Reviews, Vol. 20. No. 3, December 2000)

"...I was impressed with this book..." (The Statistician, Vol.51, No.2 2002) 

"...excellent for the audience to whom it is addressed, and it is to be hoped that the author will write a further textbook..." (Jnl of the Operational Research Society, Vol 54(10) 2003)

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Product Details

Table of Contents

DETERMINISTIC MODELS.
Multi-Stage Decision Problems.
Networks.
Further Applications.
Convexity.
STOCHASTIC MODELS.
Markov Systems.
Optimal Stopping.
Special Problems.
MARKOV DECISION PROCESSES.
General Theory.
Minimizing Average Costs.
Statistical Decisions.
Notes on the Exercises.
References.
Index.
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