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Fuzzy Sets for Words: WhyType-2 Fuzzy Sets Should beUsed and How They Can beUsed

Jerry M. Mendel

University of Southern California

Los Angeles, CA 90089-2564

Copyright Jerry M. Mendel

Note: This was presented as a two-hour tutorial at IEEE FUZZ in BudapestHungary in 2004. I have made some modifications to it, and have added notes tomost of the slides so that it now serves as a more useful on-line learningexperience.

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Outline of Tutorial

I. Refutation of type-1 fuzzy sets as modelsfor words (p. 3)

II. Interval type-2 fuzzy sets (p. 18)

III. Fuzzy sets for words (p. 29)

IV. Rule-based interval type-2 fuzzy logicsystems (p. 48)

V. Two applications (p. 77)

VI. Conclusions (p. 95)

VII. References (p. 99)

Each of the listed major sections of this tutorial will be preceded by a title page.The page on which a new section begins is shown in parentheses after the title ofthat section.

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Part I: Refutation of type-1fuzzy sets as models forwords

Some people may find this section very controversial. I will make some furthercomments about this later.

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Fuzzy Sets

In 1965, Lotfi Zadehpublished the first paperabout fuzzy sets

Opened up a new andimportant field that has

withstood the tests oftime (>30,000 articles)

If I have nothing to add to what is on the slide, the accompanying notes page willbe blank.

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Fuzzy Set Defined

Unlike a crisp set whose MF takeson only two values 0 or 1, the MF ofa fuzzy set can range between 0

and 1

A = x,A(x)( ) x !X,0 " A (x) " 1{ }

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0

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MF: Membership function

The equation for A defines the fuzzy set by means of its MF.

Shown on this slide are two well-known examples of a MF, a trapezoid and atriangle.

It is now becoming popular to refer to the fuzzy set that is defined on this slideas a "type-1 fuzzy set," because people are also working with "type-2 fuzzysets."

We will have a lot more to say about type-2 fuzzy sets later in this tutorial.

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Fuzzy Sets as Mathematics

Beginning with the MF definition of a fuzzyset, we can develop lots of interestingmathematics

We never have to associate a fuzzy setwith a word to do this

It can all be done using the formaldefinition of a fuzzy set

When we associate a fuzzy set with aword we are, in effect, using it to model aword

Distinguishing between mathematics and applications of it as models ofdifferent kinds of physical situations is not a new idea.

Consider, for example, differential equations, which can be studied entirelywithin the framework of mathematics, or as models for physical systems.

The study of differential equations within the framework of mathematics is well-established. It covers issues such as existence and uniqueness of solution,solutions, etc.

It is through the use of scientifically accepted principles (e.g. Newton's Laws,Kirchoff's Laws) that we are led to differential equation models for mechanical,electrical, etc. systems.

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Fuzzy Sets Used to ModelWords

Fuzzy sets used to model words can be

interpreted as a scientific theory, asdistinct from fuzzy sets as mathematics

Is the use of fuzzy sets to model wordsscientific?

If so, is it a correct scientific theory?

When fuzzy sets are used in situations where they are not modeling words, thenthese questions are not usually (have not been) asked.

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Falsificationism

A theory is scientific only if it isrefutable by a conceivable event.Every genuine test of a scientifictheory, then, is logically anattempt to refute or to falsify it,and one genuine counterinstance falsifies the wholetheory.

Sir Karl Popper(1902-1994)

Ref.: Karl Popper, The Logic of Scientific Discovery, Hutchinson, London, 1959

According to the Stanford Encyclopedia of Philosophy, "Karl Popper isgenerally regarded as one of the greatest philosophers of science of this (20th)century." For information about him, go to:

http://plato.stanford.edu/entries/popper

On the Karp Popper Web (http://www.eeng.dcu.ie/~tkpw), it is stated that:"Falsificationism is the idea that science advances by unjustified exaggeratedguesses followed by unstinting criticism. Only hypotheses capable of clashingwith observation reports are allowed to count as scientific."

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Popper Meet Zadeh

Yes, I model words using

fuzzy sets

Is this scientific?

And, if sois it scientifically

correct?

I will now use Popper's Falsificationism to answer the question "Is itscientifically correct to model words using fuzzy sets?"

But first I will ask the question "Who among us has not used word examples forfuzzy sets?

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Who Among Us Has Not UsedWord Examples For FuzzySets? In his 1965 paper, Zadehs first example of a

fuzzy set connected it to a word

We all do this! We dont have to do it! MF pictures can be drawn without attaching

a word label to the fuzzy set

Just choose a function for the MF and thensketch it 1

0

This is not meant to be an attack on fuzzy sets. Some people may havemisinterpreted it as such. It may be the first time someone has questionedZadeh's use of fuzzy sets as models for words.

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Back to Our Two Questions

Is the use of fuzzy sets to modelwords scientific? For a theory to be called scientific it

must be testable

If so, is it a correct scientific theory? A scientific theory can be correct or

incorrect Newtons theory of gravitation vs. Einsteins General

Theory of Relativity

Some theories are not scientific because they are not testable, e.g., astrology,phrenology.

However, a theory that is scientific can be correct or incorrect.

Until a "correct" scientific theory is refuted it remains accepted as a correctscientific theory. Once it has been refuted, it is replaced by the new "correct"scientific theory, which then waits to be refuted.

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Fuzzy Sets for Words AreScientific: 1

Methods have been described in theFS literature to elicit knowledge frompeople for the construction of a MF Polling

Interval estimation

Direct rating

Reverse rating

Transition interval estimation

Most engineering applications of fuzzy sets do not construct a MF by surveyingpeople and using any of these knowledge elicitation methods.

Going from knowledge elicited from people to a MF is an "inverse problem."

In most engineering applications of fuzzy sets we choose the shape of the MFand either pre-specify its parameters or we "learn" its parameters through anoptimization procedure that uses application-based data (e.g., a temperatureprofile), but not elicited MF data.

A reference for some of these knowledge elicitation methods is: I. B. Trksen, Measurement of Membership Functions and Their Acquisition, Fuzzy Setsand Systems, vol. 40, pp. 5-38, 1991 (especially Section 5).

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Fuzzy Sets for Words AreScientific: 2

Because data can be obtained frompeople, this permits us to test fuzzysets as models for words, i.e to

attempt to refute or falsify thescientific theory of fuzzy sets asmodels for words

So, the previous work on how to collect data from people and then use it toobtain type-1 MFs makes Zadeh's "Type-1 fuzzy sets as a model for words"scientific.

But, remember a scientific theory can be correct or incorrect.

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Type-1 Fuzzy Setsas Models for Wordsis Scientifically Incorrect

A fuzzy set for a word is a well-definedtype-1 FS that is totally certain once all ofits parameters are specified

Words mean different things to differentpeople, and so are uncertain

It is a contradiction to say that somethingcertain can model something that isuncertain

This slide contains a simple three-step refutation of type-1 fuzzy sets as a modelfor words.

Again, some may find this very controversial. It does not refute fuzzy sets asmathematics or its use in most applications (e.g., fuzzy logic control, rule-basedclassification, etc.). It has only refuted type-1 fuzzy sets as models for words,and therefore calls their use into question in the application of "computing withwords."

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In the Words of Popper

Associating the originaltype-1 FS with a word isa conceivable eventthat has provided acounter-instance thatfalsifies this approachto fuzzy sets as modelsfor words

We needed a basis for exploring whether or not type-1 fuzzy sets as a model forwords is or is not scientifically correct. Popper's widely acceptedFalsificationism provided us with such a basis.

Zadeh has suggested that type-1 fuzzy sets can be used as a model for a"prototypical word." Such a model does not capture the uncertainties in a word;however, if a study does not require such uncertainties to be used (e.g.,propagated through a rule-based system) then one may be able to use a type-1fuzzy set model for a word.

This is analogous to determinism versus randomness. If one chooses to ignorethe presence of random uncertainties, he/she can work within the framework ofdeterminism. Whether or not this is correct, depends upon the objectives of aspecific study.

When a system that is designed using fuzzy logic is going to interact directlywith people using words, then it is important to use a fuzzy set model for thewords that captures the fact that words mean different things to different people.A type-1 fuzzy set model for