Re: literature on fuzzy logic in AI


Subject: Re: literature on fuzzy logic in AI
From: Allan Kaminsky (allan@ieee.org)
Date: Mon Nov 13 2000 - 12:56:20 MET


Just to note that the hyperlink should be:

http://users.aol.com/wsiler/

Allan

At 11:23 AM 11/10/2000, WSiler@aol.com wrote:

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>In a message dated 11/9/00 5:14:06 AM Central Standard Time, jdagys@tennis.lt
>writes:
>
>
> > could anyone please recommend any texts that would
> > discuss the potential/use of fuzzy logic in AI research more generally,
> > instead of developing particular fuzzy controller or expert system?
> >
>
> >From an AI viewpoint, the main advantage of fuzzy systems theory is that
>fuzzy sets permit handling both ambiguities and contradictions. For example,
>if we have a fuzzy set with members Ford, Mercedes and Chevrolet. Our
>reasoning process has assigned grades of membership Ford 0.972, Mercedes
>0.058 and Chevrolet 0.968. We are fairly sure that Mercedes is not true, but
>cannot confidently distinguish between Ford and Chevrolet. Since all three
>possibilities are mutually exclusive, Ford and Chevrolet cannot both be true;
>we have a contradiction. If, however, our possibilities were Undesirable (0),
>Somewhat-Desirable (.87) and Very-Desirable (.83), Somewhat-Desirable and
>Very-Desirable might both be true to some extent; in this case we have an
>ambiguity.
>
>There is a short manual Building Fuzzy Expert Systems on my Web page
>http://users/aol.com/wsiler/ which deals with this topic in more detail.
>While the manual leans on our fuzzy expert system shell FLOPS, the principles
>are not dependent on any particular system.
>
>William Siler
>
>
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>In a message dated 11/9/00 5:14:06 AM Central Standard Time, jdagys@tennis.lt
>writes:
>
>
>>could anyone please recommend any texts that would
>>discuss the potential/use of fuzzy logic in AI research more generally,
>>instead of developing particular fuzzy controller or expert system?
>
>
> From an AI viewpoint, the main advantage of fuzzy systems theory is that
>fuzzy sets permit handling both ambiguities and contradictions. For example,
>if we have a fuzzy set with members Ford, Mercedes and Chevrolet. Our
>reasoning process has assigned grades of membership Ford 0.972, Mercedes
>0.058 and Chevrolet 0.968. We are fairly sure that Mercedes is not true, but
>cannot confidently distinguish between Ford and Chevrolet. Since all three
>possibilities are mutually exclusive, Ford and Chevrolet cannot both be true;
>we have a contradiction. If, however, our possibilities were Undesirable (0),
>Somewhat-Desirable (.87) and Very-Desirable (.83), Somewhat-Desirable and
>Very-Desirable might both be true to some extent; in this case we have an
>ambiguity.
>
>There is a short manual Building Fuzzy Expert Systems on my Web page
>http://users/aol.com/wsiler/ which deals with this topic in more detail.
>While the manual leans on our fuzzy expert system shell FLOPS, the principles
>are not dependent on any particular system.
>
>William Siler
>
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>
>
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