Learning control for production machine
Yu Guang Zhong · Ghent University Academic Bibliography (Ghent University) · 2010
Genetic Algorithms (GAs) are generally used as an optimization technique to search the global optimum of a function. However, this is not the only possible use for GAs. Other fields of applications where robustness and global optimization are needed could also benefit greatly from the use of GAs. The two most important domains using GAs as the underlying methodology are Genetic Based Machine Learning (GBML) [1] and Genetic Programming [2]. There has been a growing interest in applying evolution programming techniques to machine learning. This was due to the attractive idea that chromosomes, representing knowledge, are treated as data to be manipulated by genetic operators, and, at the same time, as executable code to be used in performing some task.