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

Sequential Stochastic Optimization

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£196.95

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Hardback by R. Cairoli , Robert C. Dalang

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Sequential Stochastic Optimization provides mathematicians andapplied researchers with a well-developed framework in whichstochastic optimization problems can be formulated and solved.Offering... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 13/02/1996
    ISBN13: 9780471577546, 978-0471577546
    ISBN10: 0471577545

    Number of Pages: 352

    Non Fiction , Mathematics & Science , Education

    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

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