Scalable Optimization via Probabilistic Modeling - From Algorithms to Applications (Paperback, Softcover reprint of hardcover 1st ed. 2006)

I'm not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you're going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolutionary compu- tion over the last decade or so: estimation of distribution algorithms (EDAs). EDAs borrow evolutionary computation's population orientation and sel- tionism and throw out the genetics to give us a hybrid of substantial power, elegance, and extensibility. The article sequencing in most edited volumes is hard to understand, but from the get go the editors of this volume have assembled a set of articles sequenced in a logical fashion. The book moves from design to e?ciency enhancement and then concludes with relevant applications. The emphasis on e?ciency enhancement is particularly important, because the data-mining perspectiveimplicitinEDAsopensuptheworldofoptimizationtonewme- ods of data-guided adaptation that can further speed solutions through the construction and utilization of e?ective surrogates, hybrids, and parallel and temporal decompositions.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Studies in Computational Intelligence, 33
Release date:	November 2010
First published:	2006
Editors:	Martin Pelikan • Kumara Sastry • Erick Cantu-Paz
Dimensions:	235 x 155 x 19mm (L x W x T)
Format:	Paperback
Pages:	349
Edition:	Softcover reprint of hardcover 1st ed. 2006
ISBN-13:	978-3-642-07116-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-642-07116-3
Barcode:	9783642071164

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