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Fuzzy logic and the goals of artificial intelligence

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Page 1: Fuzzy logic and the goals of artificial intelligence

"FUZZY Sets, Fuzzy Logic and the Goals of Artificial Intelligence"

Anca Ralescu

Laboratory for International Fuzzy Engineering, Siber Hegner Building 3F1, 89- 1 Yamashita-cho, Naka-ku Yokohama 231, Japan

and Computer Science Department, University of Cincinnati, Cincinnati, Ohio 4522 1, U.S.A.

The central issues in the study of intelligent systems include those of knowledge representation, leaning and reasoning. The treatment of these issues becomes more complex when uncertainty and imprecision must be taken into account.

We discuss the tradeoff in accuracy versus flexibility and we argue that when immediate, practical results are of primary concem the usual desire for accuracy and formal treatment decreases.

In this lecture we investigate some of the goals of artificial intelligence and the limitations of the purely symbolic approach.

Altemative approaches including neural networks, probabilistic methods, and fuzzy techniques have been sought and experimented with. The lecture will focus on the relevance of fuzzy logic to the treatment of knowledge representation, learning and inference.

We propose that, rather than oppose diverse theories in a fruitless confrontation, their integration can result in a more powerful approach to the study of intelligent systems.

The use of fuzzy sets for knowledge representation, and of fuzzy logic for inference under uncertainty (with or without a probabilistic method as the problem in hand may require) is illustrated. The advantage of combining fuzzy and neural network techniques is also discussed. We point out that a collection of new computing methods, globally known as soft computing, may indeed lead us closer to the goals of artificial intelligence.

From a converse point of view, starting from the goals of intelligent systems we submit that the current fuzzy methodology must also be augmented.

The underlying idea of OUT discussion is that fuzzy sets theory, fuzzy logic and associated techniques provide an excellent tool for interfacing the real world of measurments, and the conceptual world embodied by language.

136 0-81864260-2/93 $03.00 0 1993 IEEE