Stochastic Approximation A Dynamical Systems Viewpoint
Description
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.
Keywords
Mathematics
2009Book
Author(s)Vivek S. Borkar
PublisherHindustan Book Agency
ISBN9788185931852
LanguageEnglish
