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Traditionaly, fuzzy logic has been viewed in the AI community as an approach for managing uncertainty. In the 1990's, however, fuzzy logic has emerged as a paradigm for approximating a functional mapping. This complementary mordern view about the technology offers new insights about the foundation of fuzzy logic as well as new challenges regarding the identification of fuzzy models. In this paper, we will first review some of the major milestones in the history of developing fuzzy logic technology. After a short summary of major concepts in fuzzy logic, we discuss a mordern view about the foundation of two types of fuzzy rules. Finally, we review some of the research in addressing various challenges regarding automated identification of fuzzy rule-based models.