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- 164pages
- 6 heures de lecture
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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.
Achat du livre
Stochastic Approximation, Vivek S. Borkar
- Langue
- Année de publication
- 2008
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- Langue
- Anglais
- Auteurs
- Vivek S. Borkar
- Publié
- 2008
- Format
- rigide
- Pages
- 164
- ISBN10
- 0521515920
- ISBN13
- 9780521515924
- Séries
- Évaluation
- 4 sur 5
- 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.