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Hierarchical Bayesian Optimization Algorithm By Martin Pelikan

Hierarchical Bayesian Optimization Algorithm by Martin Pelikan

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Summary

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.

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Hierarchical Bayesian Optimization Algorithm Summary

Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms by Martin Pelikan

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.

Table of Contents

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.

Additional information

NLS9783642062735
9783642062735
3642062733
Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms by Martin Pelikan
New
Paperback
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
2010-10-21
166
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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