Machine Learning for Evolution Strategies

Autori

• Oliver Kramer

Parametri

• 124 pagine
• 5 ore di lettura

• Computer, IT, programmazione

Maggiori informazioni sul libro

Focusing on the intersection of machine learning and evolution strategies, this book presents a variety of algorithmic hybridizations that enhance optimization processes. It covers techniques such as covariance matrix estimation, meta-modeling, and clustering-based niching. With a strong emphasis on practical application, experiments utilize a (1+1)-ES implemented in Python with scikit-learn, addressing benchmark problems to illustrate key concepts. The text also explores broader research implications, bridging theoretical frameworks with experimental findings.

Lingua: Inglese

Pubblicato: 2018

(In brossura)