Networks of Learning Automata: Techniques for Online Shastic Optimization is a comprehensive account of learning automata models with emphasis on multiautomata systems. It considers synthesis of complex learning structures from simple building blocks and uses shastic algorithms for refining probabilities of selecting actions. Mathematical analysis of the behavior of games and feedforward networks is provided. Algorithms considered here can be used for online optimization of systems based on noisy measurements of performance index. Also, algorithms that assure convergence to the global optimum are presented. Parallel operation of automata systems for improving speed of convergence is described. The authors also include extensive discussion of how learning automata solutions can be constructed in a variety of applications.
1112225773
Networks of Learning Automata: Techniques for Online Stochastic Optimization
Networks of Learning Automata: Techniques for Online Shastic Optimization is a comprehensive account of learning automata models with emphasis on multiautomata systems. It considers synthesis of complex learning structures from simple building blocks and uses shastic algorithms for refining probabilities of selecting actions. Mathematical analysis of the behavior of games and feedforward networks is provided. Algorithms considered here can be used for online optimization of systems based on noisy measurements of performance index. Also, algorithms that assure convergence to the global optimum are presented. Parallel operation of automata systems for improving speed of convergence is described. The authors also include extensive discussion of how learning automata solutions can be constructed in a variety of applications.
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Networks of Learning Automata: Techniques for Online Stochastic Optimization
268
Networks of Learning Automata: Techniques for Online Stochastic Optimization
268Paperback(Softcover reprint of the original 1st ed. 2004)
$109.99
109.99
In Stock
Product Details
ISBN-13: | 9781461347750 |
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Publisher: | Springer US |
Publication date: | 09/28/2012 |
Edition description: | Softcover reprint of the original 1st ed. 2004 |
Pages: | 268 |
Product dimensions: | 6.10(w) x 9.25(h) x 0.02(d) |
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