Author(s): R. Cairoli (Author), Robert C. Dalang (Author)
Publisher: Wiley-Interscience
Publication Date: February 2, 1996
Edition: 1st
Language: English
Print length: 352 pages
ISBN-10: 0471577545
ISBN-13: 9780471577546
Book Description
Sequential Stochastic Optimization provides mathematicians andapplied researchers with a well-developed framework in whichstochastic optimization problems can be formulated and solved.Offering much material that is either new or has never beforeappeared in book form, it lucidly presents a unified theory ofoptimal stopping and optimal sequential control of stochasticprocesses. This book has been carefully organized so that littleprior knowledge of the subject is assumed; its only prerequisitesare a standard graduate course in probability theory and somefamiliarity with discrete-parameter martingales.
Major topics covered in Sequential Stochastic Optimization include: * Fundamental notions, such as essential supremum, stopping points,accessibility, martingales and supermartingales indexed by INd * Conditions which ensure the integrability of certain suprema ofpartial sums of arrays of independent random variables * The general theory of optimal stopping for processes indexed byInd * Structural properties of information flows * Sequential sampling and the theory of optimal sequential control * Multi-armed bandits, Markov chains and optimal switching betweenrandom walks
Editorial Reviews
From the Publisher
Presents a unified mathematical theory of optimal stopping and sequential control of stochastic processes along with several applications including sequential statistical tests involving several populations and multi-armed bandit problems. The material is accompanied by extensive problems, exercises and realistic examples which facilitate understanding. Contains a large amount of original information unavailable elsewhere.
From the Inside Flap
Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-parameter martingales.
Major topics covered in Sequential Stochastic Optimization include:
Fundamental notions, such as essential supremum, stopping points, accessibility, martingales and supermartingales indexed by INd
Conditions which ensure the integrability of certain suprema of partial sums of arrays of independent random variables
The general theory of optimal stopping for processes indexed by Ind
Structural properties of information flows
Sequential sampling and the theory of optimal sequential control
Multi-armed bandits, Markov chains and optimal switching between random walks
From the Back Cover
Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-parameter martingales.
Major topics covered in Sequential Stochastic Optimization include:
Fundamental notions, such as essential supremum, stopping points, accessibility, martingales and supermartingales indexed by INd
Conditions which ensure the integrability of certain suprema of partial sums of arrays of independent random variables
The general theory of optimal stopping for processes indexed by Ind
Structural properties of information flows
Sequential sampling and the theory of optimal sequential control
Multi-armed bandits, Markov chains and optimal switching between random walks
About the Author
R. Cairoli and Robert C. Dalang are the authors of Sequential Stochastic Optimization, published by Wiley.
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