Machine Learning for Evolution Strategies

By:

Oliver Kramer

Format:

Hardback

Series:

Studies in Big Data

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Description

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.

Release date NZ

June 6th, 2016

Author

Oliver Kramer

Audiences

Professional & Vocational
Tertiary Education (US: College)

Edition

1st ed. 2016

Illustrations

38 Illustrations, color; IX, 124 p. 38 illus. in color.

Pages

124

Series

Studies in Big Data

Dimensions

155x235x10

ISBN-13

9783319333816

Product ID

25061872

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