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Tuning Metaheuristics: A Machine Learning Perspective PDF

225 Pages·2009·1.738 MB·English
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by Mauro Birattari (auth.)| 2009| 225 pages| 1.738| English

About Tuning Metaheuristics: A Machine Learning Perspective

The importance of tuning metaheuristics is widely acknowledged in scientific literature. However, there is very little dedicated research on the subject. Typically, scientists and practitioners tune metaheuristics by hand, guided only by their experience and by some rules of thumb. Tuning metaheuristics is often considered to be more of an art than a science.This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning. By adopting a machine learning perspective, the author gives a formal definition of the tuning problem, develops a generic algorithm for tuning metaheuristics, and defines an appropriate experimental methodology for assessing the performance of metaheuristics.

Detailed Information

Author:Mauro Birattari (auth.)
Publication Year:2009
ISBN:9783642004834
Pages:225
Language:English
File Size:1.738
Format:PDF
Price:FREE
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