TY - BOOK ID - 107478739 TI - Tuning Metaheuristics : A Machine Learning Perspective AU - Birattari, Mauro AU - SpringerLink (Online service) PY - 2009 SN - 9783642004834 PB - Berlin Heidelberg Springer Berlin Heidelberg DB - UniCat KW - Engineering sciences. Technology KW - Artificial intelligence. Robotics. Simulation. Graphics KW - analyse (wiskunde) KW - machine learning KW - ingenieurswetenschappen KW - robots UR - https://www.unicat.be/uniCat?func=search&query=sysid:107478739 AB - 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. ER -