fuzzy logic (fuz`ê
A form of logic used in some expert systems and other artificial-intelligence applications in which variables can have degrees of truthfulness or falsehood represented by a range of values between 1 (true) and 0 (false). With fuzzy logic, the outcome of an operation can be expressed as a probability rather than as a certainty. For example, an outcome might be probably true, possibly true, possibly false, or probably false.
Fuzzy Logic, form of computer
logic used in some expert systems and other artificial intelligence programs.
Data for such applications is often not simply present or absent, true
or false. Fuzzy logic allows a computer to calculate with a range of comparative
values, approximately as human beings estimate likelihoods. Fuzzy logic
may indicate a degree of probability rather than a single quantitative
or logical result.
first mention of Fuzzy Logic in Usenet:
From: LENAT@SU-SCORE.ARPA@sri-unix.UUCP (LENAT@SU-SCORE.ARPA@sri-unix.UUCP)
Subject: Colloquium Oct 11: ZADEH
Date: 1983-10-06 20:18:09 PST
From: Doug Lenat <LENAT@SU-SCORE.ARPA>
[Reprinted from the SU-SCORE bboard.]
Professor Lotfi Zadeh, of UCB, will be giving the CS colloquium this Tuesday (10/11). As usual, it will be in Terman Auditorium, at 4:15 (preceded at 3:45 by refreshments in the 3rd floor lounge of Margaret Jacks Hall).
The title and abstract for the colloquium are as follows:
Reasoning With Commonsense Knowledge
Commonsense knowledge is exemplified by "Glass is brittle," "Cold is infectious," "The rich are conservative," "If a car is old, it is unlikely to be in good shape," etc. Such knowledge forms the basis for most of human reasoning in everyday situations.
Given the pervasiveness of commonsense reasoning, a question which begs for answer is: Why is commonsense reasoning a neglected area in classical logic? Because, almost by definition, commonsense knowledge is that knowledge which is not representable as a collection of well-formed formulae in predicate logic or other logical systems which have the same basic conceptual structure as predicate logic.
The approach to commonsense reasoning which is described in the talk is based on the use of fuzzy logic -- a logic which allows the use of fuzzy predicates, fuzzy quantifiers and fuzzy truth-values. In this logic, commonsense knowledge is defined to be a collection of dispositions, that is propositions with suppressed fuzzy quantifiers. To infer from such knowledge, three basic syllogisms are developed: (1) the intersection/product syllogism; (2) the consequent conjunction syllogism; and (3) the antecedent conjunction syllogism. The use of these syllogisms in commonsense reasoning and their application to the combination of evidence in expert systems is discussed and illustrated by examples.