Stochastic Approximation

This simple, compact toolkit for designing and analyzing stochastic approximation algorithms requires only a basic understanding of probability and differential equations. Although powerful, these algorithms have applications in control and communications engineering, artificial intelligence and economic modeling. Unique topics include finite-time behavior, multiple timescales and asynchronous implementation. There is a useful plethora of applications, each with concrete examples from engineering and economics. Notably it covers variants of stochastic gradient-based optimization schemes, fixed-point solvers, which are commonplace in learning algorithms for approximate dynamic programming, and some models of collective behavior.

Author: Vivek S. Borkar
Publisher: Cambridge University Press
Published: 07/01/2008
Pages: 176
Binding Type: Hardcover
Weight: 0.85lbs
Size: 9.00h x 6.00w x 0.60d
ISBN: 9780521515924

About the Author
Borkar, Vivek S.: - Vivek S. Borkar is dean of the School of Technology and Computer Science at the Tata Institute of Fundamental Research. A distinguished researcher in stochastic and adaptive control, he distils his deep knowledge and broad experience in this motivating book.