Stochastic Approximation: A Dynamical Systems Viewpoint
Vivek S. Borkar
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.
Categorie:
Anno:
2008
Edizione:
1
Lingua:
english
Pagine:
176
ISBN 10:
0521515920
ISBN 13:
9780521515924
File:
PDF, 824 KB
IPFS:
,
english, 2008
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