Download Machine Learning for Evolution Strategies (Studies in Big by Oliver Kramer PDF

By Oliver Kramer

This book
introduces various algorithmic hybridizations among either worlds that show
how computing device studying can enhance and aid evolution recommendations. The set of
methods contains covariance matrix estimation, meta-modeling of health and
constraint features, dimensionality aid for seek and visualization of
high-dimensional optimization procedures, and clustering-based niching. After
giving an advent to evolution recommendations and computing device studying, the book
builds the bridge among either worlds with an algorithmic and experimental
perspective. Experiments typically hire a (1+1)-ES and are applied in Python
using the computing device studying library scikit-learn. The examples are carried out on
typical benchmark difficulties illustrating algorithmic recommendations and their
experimental habit. The publication closes with a dialogue of comparable strains of
research.

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