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Membership queries extended with the meta query concept is proposed as a method to acquire complex classification rules. Furthermore, relevent concept classes, where a small number of queries is sufficient, are characterized. In this paper we advocate and present the benefits of the use of queries in order to learn a target concept efficiently. Thus providing the foundations for automating the knowledge acquisition process. Based on these results, we developed a knowledge acquisition tool KAC-Zdblp:conf/ijcai/HoffmanT91 fatcat:exc64cmizncf5kq5kwxuffeytu