Sequential Stochastic Optimization / Edition 1 available in Hardcover
- Pub. Date:
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
About the Author
R. Cairoli and Robert C. Dalang are the authors of Sequential Stochastic Optimization, published by Wiley.
Table of Contents
Sums of Independent Random Variables.
Reduction to a Single Dimension.
Accessibility and Filtration Structure.
Optimal Sequential Control.
The Markovian Case.
Optimal Switching Between Two Random Walks.