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Machine Learning for Evolution Strategies

Language EnglishEnglish
Book Paperback
Book Machine Learning for Evolution Strategies Oliver Kramer
Libristo code: 19703722
Publishers Springer International Publishing AG, May 2018
This book introduces numerous algorithmic hybridizations between both worlds that show how machine l... Full description
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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.

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About the book

Full name Machine Learning for Evolution Strategies
Author Oliver Kramer
Language English
Binding Book - Paperback
Date of issue 2018
Number of pages 124
EAN 9783319815008
ISBN 9783319815008
Libristo code 19703722
Publishers Springer International Publishing AG
Weight 2175
Dimensions 155 x 235 x 7

Categories

Reference, Information & Interdisciplinary subjects > Research & information: general > Information theory > Cybernetics & systems theory
Computing & Information Technology > Databases > Data mining
Computing & Information Technology > Computer science > Computer modelling & simulation
Computing & Information Technology > Computer science > Artificial intelligence
Mathematics & Science > Science: general issues
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