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Fuzzy Logic
This nOde last updated November 27th, 2004 and is permanently morphing...
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fuzzy logic

fuzzy logic (fuz`ê loj'ik) noun
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

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.

• game theory
• book _Fuzzy Thinking_ by Bart Kosko
• 604 track _Double Barrel_ by Fuzzy Logic off of _Trancentral 7_ on Kickin
• track _I, Fuzzbot_ MP3 by Brainiac off of _Smack Bunny Baby_ 12" on Grass (1993)
• worldbeat trip hop track _Fuzzy Freaky_ MP3 by David Byrne off of _Feelings_ on Luaka Bop (1997)
• track _Wiggly World_ MP3 by Devo off of _Duty Now For The Future_ 12"   on Warner Brothers (1979)

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
Newsgroups: net.ai
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.

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