資料來源 : WordNet®

fuzzy logic
     n : a form of mathematical logic in which truth can assume a
         continuum of values between 0 and 1

資料來源 : Free On-Line Dictionary of Computing

fuzzy logic
     
        A superset of {Boolean logic} dealing with the concept of
        partial truth -- {truth value}s between "completely true" and
        "completely false".  It was introduced by Dr. Lotfi Zadeh of
        {UCB} in the 1960's as a means to model the uncertainty of
        {natural language}.
     
        Any specific theory may be generalised from a discrete (or
        "crisp") form to a continuous (fuzzy) form, e.g. "fuzzy
        calculus", "fuzzy differential equations" etc.  Fuzzy logic
        replaces Boolean truth values with degrees of truth which are
        very similar to probabilities except that they need not sum to
        one.  Instead of an assertion pred(X), meaning that X
        definitely has the property associated with {predicate}
        "pred", we have a truth function truth(pred(X)) which gives
        the degree of truth that X has that property.  We can combine
        such values using the standard definitions of fuzzy logic:
     
        	truth(not x)   = 1.0 - truth(x)
        	truth(x and y) = minimum (truth(x), truth(y))
        	truth(x or y)  = maximum (truth(x), truth(y))
     
        (There are other possible definitions for "and" and "or",
        e.g. using sum and product).  If truth values are restricted to
        0 and 1 then these functions behave just like their Boolean
        counterparts.  This is known as the "extension principle".
     
        Just as a Boolean predicate asserts that its argument
        definitely belongs to some subset of all objects, a fuzzy
        predicate gives the degree of truth with which its argument
        belongs to a {fuzzy subset}.
     
        {Usenet} newsgroup: {news:comp.ai.fuzzy}.
     
        E-mail servers: ,
        , .
     
        {(ftp://ftp.hiof.no/pub/Fuzzy)},
        {(ftp://ntia.its.bldrdoc.gov/pub/fuzzy)}.
     
        {FAQ
        (ftp://rtfm.mit.edu/pub/usenet-by-group/comp.answers/fuzzy-logic)}.
     
        {James Brule, "Fuzzy systems - a tutorial", 1985
        (http://life.anu.edu.au/complex_systems/fuzzy.html)}.
     
        {STB Software Catalog
        (http://krakatoa.jsc.nasa.gov/stb/catalog.html)}, includes a
        few fuzzy tools.
     
        [H.J. Zimmerman, "Fuzzy Sets, Decision Making and Expert
        Systems", Kluwer, Dordrecht, 1987].
     
        ["Fuzzy Logic, State of the Art", Ed. R. Lowen, Marc Roubens,
        Theory and Decision Library, D: System theory, Knowledge
        Engineering and Problem Solving 12, Kluwer, Dordrecht, 1993,
        ISBN 0-7923-2324-6].
     
        (1995-02-21)