Machine Learning for Evolution Strategies By: Oliver Kramer Publisher: Springer Print ISBN: 9783319333816, 331933381X eText ISBN: 9783319333830, 3319333836 Copyright year: 2016 Format: PDF Available from $ 139.00 USD SKU: 9783319333830 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. SKU: 9783319333816 Ebooks here: https://ebookscoffee.sellpass.io/products/Machine-Learning-for-Evolution-Strategies
