Can I read Machine Learning for Evolution Strategies (Studies in Big Data, 20) on EtoBox?

Machine Learning for Evolution Strategies (Studies in Big Data, 20) by Oliver Kramer (auth.) is a nonfiction available to read on EtoBox.

What is Machine Learning for Evolution Strategies (Studies in Big Data, 20) about?

"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"--Provided by publisher

Who reads Machine Learning for Evolution Strategies (Studies in Big Data, 20)?

Author

Oliver Kramer (auth.)

Publisher

Springer International Publishing AG

Published

2016

Language

EN

ISBN

9783319333830

Category

nonfiction

Subjects

Computer Science, Engineering, Mathematics