Oliver Kramer

Machine Learning for Evolution Strategies

• Broschiertes Buch

Produktbeschreibung

This bookintroduces numerous algorithmic hybridizations between both worlds that showhow machine learning can improve and support evolution strategies. The set ofmethods comprises covariance matrix estimation, meta-modeling of fitness andconstraint functions, dimensionality reduction for search and visualization ofhigh-dimensional optimization processes, and clustering-based niching. Aftergiving an introduction to evolution strategies and machine learning, the bookbuilds the bridge between both worlds with an algorithmic and experimentalperspective. Experiments mostly employ a (1+1)-ES and are implemented in Pythonusing the machine learning library scikit-learn. The examples are conducted ontypical benchmark problems illustrating algorithmic concepts and theirexperimental behavior. The book closes with a discussion of related lines ofresearch.

Produktdetails

• Studies in Big Data 20
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-81500-8
• Softcover reprint of the original 1st ed. 2016
• Seitenzahl: 124
• Englisch
• Abmessung: 7mm x 155mm x 235mm
• Gewicht: 219g
• ISBN-13: 9783319815008
• ISBN-10: 3319815008
• Artikelnr.: 53472926

Inhaltsangabe

Part I Evolution Strategies.- Part II Machine Learning.- Part III Supervised Learning.

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Part I Evolution Strategies.- Part II Machine Learning.- Part III Supervised Learning.