Hierarchical Bayesian Optimization Algorithm

Toward a New Generation of Evolutionary Algorithms

Specificaties
Gebonden, 166 blz. | Engels
Springer Berlin Heidelberg | 2005e druk, 2005
ISBN13: 9783540237747
Rubricering
Springer Berlin Heidelberg 2005e druk, 2005 9783540237747
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9783540237747
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:166
Uitgever:Springer Berlin Heidelberg
Druk:2005

Inhoudsopgave

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.

Rubrieken

    Personen

      Trefwoorden

        Hierarchical Bayesian Optimization Algorithm