Stochastic Approximation

Autori

• Vivek S. Borkar

Parametri

• 164 pagine
• 6 ore di lettura

• Matematica

Maggiori informazioni sul libro

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.

Lingua: Inglese

Pubblicato: 2008

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