Machine Learning for Evolution Strategies

Autor*innen

• Oliver Kramer

Parameter

• 124 Seiten
• 5 Lesestunden

• Informatik & Programmierung

Mehr zum Buch

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.

• Sprache: Englisch
• Erscheinungsdatum: 2018
• Einband: Paperback