Decision Theory: An Introduction to Dynamic Programming and Sequential Decisions

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9780471976493: Decision Theory: An Introduction to Dynamic Programming and Sequential Decisions
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Decision Theory An Introduction to Dynamic Programming andSequential Decisions John Bather University of Sussex, UKMathematical induction, and its use in solving optimizationproblems, is a topic of great interest with many applications. Itenables us to study multistage decision problems by proceedingbackwards in time, using a method called dynamic programming. Allthe techniques needed to solve the various problems are explained,and the author's fluent style will leave the reader with an avidinterest in the subject.
* Tailored to the needs of students of optimization and decisiontheory
* Written in a lucid style with numerous examples andapplications
* Coverage of deterministic models: maximizing utilities, directednetworks, shortest paths, critical path analysis, scheduling andconvexity
* Coverage of stochastic models: stochastic dynamic programming,optimal stopping problems and other special topics
* Coverage of advanced topics: Markov decision processes,minimizing expected costs, policy improvements and problems withunknown statistical parameters
* Contains exercises at the end of each chapter, with hints in anappendix
Aimed primarily at students of mathematics and statistics, thelucid text will also appeal to engineering and science students andthose working in the areas of optimization and operations research.

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"This textbook...draws on his many years of experience in teachingthis topic as well as on his considerable professional expertise inthe area. It is ideally suited to its stated purpose as a studenttext." (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 itis 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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9780471976486: Decision Theory: An Introduction to Dynamic Programming and Sequential Decisions

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ISBN 10:  0471976482 ISBN 13:  9780471976486
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Book Description John Wiley and Sons Ltd, United Kingdom, 2000. Paperback. Condition: New. 1. Auflage. Language: English. Brand new Book. Decision Theory An Introduction to Dynamic Programming and Sequential Decisions John Bather University of Sussex, UK Mathematical induction, and its use in solving optimization problems, is a topic of great interest with many applications. It enables us to study multistage decision problems by proceeding backwards in time, using a method called dynamic programming. All the techniques needed to solve the various problems are explained, and the author's fluent style will leave the reader with an avid interest in the subject. Tailored to the needs of students of optimization and decision theory Written in a lucid style with numerous examples and applications Coverage of deterministic models: maximizing utilities, directed networks, shortest paths, critical path analysis, scheduling and convexity Coverage of stochastic models: stochastic dynamic programming, optimal stopping problems and other special topics Coverage of advanced topics: Markov decision processes, minimizing expected costs, policy improvements and problems with unknown statistical parameters Contains exercises at the end of each chapter, with hints in an appendix Aimed primarily at students of mathematics and statistics, the lucid text will also appeal to engineering and science students and those working in the areas of optimization and operations research. Seller Inventory # AAH9780471976493

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Book Description John Wiley and Sons Ltd, United Kingdom, 2000. Paperback. Condition: New. 1. Auflage. Language: English. Brand new Book. Decision Theory An Introduction to Dynamic Programming and Sequential Decisions John Bather University of Sussex, UK Mathematical induction, and its use in solving optimization problems, is a topic of great interest with many applications. It enables us to study multistage decision problems by proceeding backwards in time, using a method called dynamic programming. All the techniques needed to solve the various problems are explained, and the author's fluent style will leave the reader with an avid interest in the subject.Tailored to the needs of students of optimization and decision theory Written in a lucid style with numerous examples and applications Coverage of deterministic models: maximizing utilities, directed networks, shortest paths, critical path analysis, scheduling and convexity Coverage of stochastic models: stochastic dynamic programming, optimal stopping problems and other special topics Coverage of advanced topics: Markov decision processes, minimizing expected costs, policy improvements and problems with unknown statistical parameters Contains exercises at the end of each chapter, with hints in an appendix Aimed primarily at students of mathematics and statistics, the lucid text will also appeal to engineering and science students and those working in the areas of optimization and operations research. Seller Inventory # AAH9780471976493

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