Title :
Fuzzy logic-a modern perspective
Author_Institution :
Dept. of Comput. Sci., Texas A&M Univ., College Station, TX, USA
Abstract :
Traditionally, fuzzy logic has been viewed in the artificial intelligence (AI) community as an approach for managing uncertainty. In the 1990s, however, fuzzy logic has emerged as a paradigm for approximating a functional mapping. This complementary modern 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 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 modern 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
Keywords :
artificial intelligence; function approximation; fuzzy logic; history; identification; inference mechanisms; reviews; uncertainty handling; approximate reasoning; artificial intelligence; automated fuzzy model identification; functional mapping approximation; fuzzy logic; fuzzy rules; history; possibility theory; review; soft computing; technology development; uncertainty management; Artificial intelligence; Computer industry; Costs; Function approximation; Fuzzy logic; Fuzzy reasoning; History; Possibility theory; Problem-solving; Uncertainty;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
