We have proposed a Coevolutionary Genetic Algorithm which consists of two GA populations; an H-GA (Host GA) and a P-GA (Parasite GA). A new Coevolutionary Genetic Algorithm is introduced with an ability of schema extraction by machine learning techniques such as C4.5 and CN2. We adopted inductive learning methods in order to extract useful schemata from H-GA. The training data for the machine learning consist of a large amount of genetic information together with their fitness values which have been examined by the H-GA. Through several computational simulations, we confirmed the effectiveness of the proposed method and have done detailed analyses of the proposed method.
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