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Hierarchical Bayesian Optimization Algorithm

Toward a New Generation of Evolutionary Algorithms

Springer Berlin,
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This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms, by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, motivates and describes BOA and hBOA in a way accessible to a wide audience, and presents numerous results confirming that they are revolutionary approaches to black-box optimization.


Titel: Hierarchical Bayesian Optimization Algorithm
Autoren/Herausgeber: Martin Pelikan
Aus der Reihe: Studies in Fuzziness and Soft Computing
Ausgabe: Softcover reprint of hardcover 1st ed. 2005

ISBN/EAN: 9783642062735

Seitenzahl: 166
Format: 23,5 x 15,5 cm
Produktform: Taschenbuch/Softcover
Gewicht: 290 g
Sprache: Englisch - Newsletter
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