Hierarchical Bayesian Optimization Algorithm Toward a New Generation of Evolutionary Algorithms

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.

Produktdetails

• Autoren: Martin Pelikan
• Verlag: Springer, Berlin
• Sprachen: Englisch
• Inhalt: Buch
• Produktform: Taschenbuch
• Erscheinungsdatum: 21.10.2010
• Thema: Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik
• EAN: 9783642062735
• ISBN: 978-3-642-06273-5
• Anzahl Seiten: 166
• Illustration: XVIII, 166 p.
• Abmessung (Verpackung): 15.6 x 23.5 x 23.4 cm
• Gewicht (Verpackung): 289 g
• Serie: Studies in Fuzziness and Soft Computing > 170
• Themen: C, Künstliche Intelligenz, Algorithmen und Datenstrukturen, Algorithms, Artificial Intelligence, Computerprogrammierung und Softwareentwicklung, Angewandte Mathematik, engineering, Theory of Computation, Applications of Mathematics, Mathematical and Computational Engineering, Programming Techniques, Computer programming, Computers, Numerical analysis, Engineering mathematics, Mathematical theory of computation, Applied mathematics, Computer programming / software engineering, Mathematical and Computational Engineering Applications, Maths for engineers