ENGLISH

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

By Armando Freitas da Rocha , Eduardo Massad , Alfredo Pereira

Book information

Publisher
Springer
Year
2005
ISBN
9783540218586, 3-540-21858-0
Open Library ID
OL9054673M
Language
english
Format
PDF
Filesize
2 MB (2181735 bytes)
Series
Studies in Fuzziness and Soft Computing
Edition
1
Pages
180\180
Library
mexmat
Time added
2009-07-20 03:45:11

Description

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.

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