Machine Learning for Evolution Strategies: 20 (Studies in Big Data, 20) - Hardcover

Book 20 of 108: Studies in Big Data

Kramer, Oliver

 
9783319333816: Machine Learning for Evolution Strategies: 20 (Studies in Big Data, 20)
Hardcover
ISBN 10: 331933381X ISBN 13: 9783319333816
Publisher: Springer, 2016

Synopsis

This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.

"synopsis" may belong to another edition of this title.

From the Back Cover

This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.

"About this title" may belong to another edition of this title.

Publisher
Springer
Publication date
2016
Language
English
ISBN 10 
331933381X
ISBN 13 
9783319333816
Binding
Hardcover
Edition number
1
Number of pages
133

Other Popular Editions of the Same Title

9783319815008: Machine Learning for Evolution Strategies: 20 (Studies in Big Data, 20)

Featured Edition

ISBN 10:  3319815008 ISBN 13:  9783319815008
Publisher: Springer, 2018
Softcover