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Résumé : This chapter introduces fuzzy logic with a review of classical logic and its operations, logical implications, and certain classical inference mechanisms such as tautologies. The ultimate goal of fuzzy logic is to form the theoretical foundation for reasoning about imprecise propositions; such reasoning has been referred to as approximate reasoning. The chapter provides the use of fuzzy sets as a calculus for the interpretation of natural language. Natural language, despite its vagueness and ambiguity, is the vehicle for human communication, and it seems appropriate that a mathematical theory that deals with fuzziness and ambiguity is also the same tool used to express and interpret the linguistic character of our language. The chapter discusses the use of natural language in the expression of a knowledge form known as rule-based systems, which shall be referred to generally as fuzzy systems. It summarizes graphical interpretation of inference, which is illustrated with some examples. Controlled Vocabulary Terms artificial intelligence; fuzzy logic; fuzzy systems