Buch, Englisch, 166 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 980 g
Toward a New Generation of Evolutionary Algorithms
Buch, Englisch, 166 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 980 g
Reihe: Studies in Fuzziness and Soft Computing
ISBN: 978-3-540-23774-7
Verlag: Springer
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms, by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, motivates and describes BOA and hBOA in a way accessible to a wide audience, and presents numerous results confirming that they are revolutionary approaches to black-box optimization.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computer-Aided Design (CAD)
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
Weitere Infos & Material
From Genetic Variation to Probabilistic Modeling.- Probabilistic Model-Building Genetic Algorithms.- Bayesian Optimization Algorithm.- Scalability Analysis.- The Challenge of Hierarchical Difficulty.- Hierarchical Bayesian Optimization Algorithm.- Hierarchical BOA in the Real World.
