Description: Hierarchical Bayesian Optimization Algorithm Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Toward a New Generation of Evolutionary Algorithms Author(s): Martin Pelikan Format: Paperback Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Germany Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K ISBN-13: 9783642062735, 978-3642062735 Synopsis 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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Book Title: Hierarchical Bayesian Optimization Algorithm
Number of Pages: 166 Pages
Language: English
Publication Name: Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms
Publisher: Springer-Verlag Berlin AND Heidelberg Gmbh & Co. KG
Publication Year: 2010
Subject: Engineering & Technology, Computer Science, Mathematics
Item Height: 235 mm
Item Weight: 290 g
Type: Textbook
Author: Martin Pelikan
Series: Studies in Fuzziness and Soft Computing
Item Width: 155 mm
Format: Paperback
