769:-
Uppskattad leveranstid 10-16 arbetsdagar
Fri frakt för medlemmar vid köp för minst 249:-
Andra format:
- Pocket/Paperback 769:-
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.
- Format: Inbunden
- ISBN: 9783540237747
- Språk: Engelska
- Antal sidor: 166
- Utgivningsdatum: 2005-02-01
- Förlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. K