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.
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Produktdetaljer
ISBN
9781483269092
Publisert
2016
Utgiver
Vendor
Academic Press
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter