Martin Pelikan

Hierarchical Bayesian Optimization Algorithm

Toward a New Generation of Evolutionary Algorithms

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Studies in Fuzziness and Soft Computing 170
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-642-06273-5
• Softcover reprint of hardcover 1st ed. 2005
• Seitenzahl: 184
• Erscheinungstermin: 21. Oktober 2010
• Englisch
• Abmessung: 235mm x 155mm x 11mm
• Gewicht: 289g
• ISBN-13: 9783642062735
• ISBN-10: 3642062733
• Artikelnr.: 32070903

Inhaltsangabe

From Genetic Variation to Probabilistic Modeling.- Probabilistic Model-Building Genetic Algorithms.- Bayesian Optimization Algorithm.- Scalability Analysis.- The Challenge of Hierarchical Difficulty.- Hierarchical Bayesian Optimization Algorithm.- Hierarchical BOA in the Real World.