Overview
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
- | Publication Date: Sep 01, 2008
- | Number of Pages: 176 pages
- | Binding: Hardback or Cased Book
- | ISBN-10: 0521515920
- | ISBN-13: 9780521515924
