Machine Learning for Evolution Strategies

[LeeAndro]

English | PDF,EPUB | 2016 | 120 Pages | ISBN : 331933381X | 7.42 MB

This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strats.​

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 strats and machine learning, the book builds the bridge between both worlds with an algorithmic and expental perspective.
Expents 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 expental behavior. The book closes with a discussion of related lines of research.



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