Talk:Fuzzy logic

Much as I respect the important contributions of Dr. Lofti Zadeh in the '60s, particularly in the reduction of an idea to engineering practice, the roots of fuzzy logic lie in the concept of "vagueness." My father Max Black published one of the seminal papers on this concept before WWII - cit.: Philosophy of Science 4, 427-455, Oct. 1937. I have brought this to Dr. Zadeh's attention and he recognizes its precedence. adamsmithusa

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Fuzzy logic describes a specific type of multi-valued logic which has gained considerable application in engineering. It warrants an article on its own, IMHO. --Robert Merkel

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Fuzzy logic is used to control household appliances (such as washing machines which sense load size and detergent concentration and auto-adjust their wash cycles accordingly; and refrigerators)

I'm not sure about the washing machines. It's not logic - it's just using the load size to calculate the detergent concentration. There is no predicate in that. The system won't be working on "how true is it that the load is heavy?". CGS 01:23, 14 Nov 2003 (UTC).

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What is this supposed to mean: "Al St.John (1893 - 1963) successfully incorporated the bearded "Fuzzy" in a series of Cowboy B-movies. See also: Westerns."? Is it a caharcter that just has the name "Fuzzy"? Or do the b-weterns by St.John somehow exemplify fuzzy logic? If that is the case the sentence should be rewritten.

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I've been adding new fuzzy logic articles: fuzzy associative matrix, Combs method, and most recently defuzzification. I decided to create these in separate pages because they can be treated in depth in their own right, although there is not much depth at these pages yet. - Furrykef 06:31, 3 Oct 2004 (UTC)

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Whether or not a statement has a certain determinate truth-value is different from whether or not we are able to know or ascertain the truth-value of a statement. Fuzzy logic is used to deal with vague concepts and predication - it is not an epistemic or doxastic modal logic used for capturing notions like degrees of certainty. Hence the deletion of the section involving the (confusion about the) "controversy" over fuzzy logic. Nortexoid 04:41, 7 Nov 2004 (UTC)

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As a statistician it is quite irritating to be told that FL is

"...generally rejected by mathematicians and statisticians because it seems to contradict the

principle of bivalence."

The idea that mathematicians, who invented undecidibility, would reject a form of logic because it involved a form of undecidibility is stupid.

FL is controversial and the critics, like myself, should be acknowledged.

The chief arguments against FL in my view are

a) Exaggerated claims are made for it. The claim that it is a generalisation of set theory is simply false, as membership functions are functions, and functions are defined in terms of sets. Thus FL is built on set theory, and is so not a generalisation of it.

b) FL is used for both deterministic purposes and decision-making under uncertainty. For deterministic purposes it does not offer much of an advantage over simple percentages. For decision-making under uncertainty it should give the same answers as decision theory or there should a good reason why not. It does not give the same answers as decision theory. The reason is that the solutions it provides are, in decision theory terms 'inadmissible' (i.e. non-optimal). FL is simply a 'quick and dirty' ad hoc technique. There is a place for 'quick and dirty' techniques in engineering, as long as one knows that that is what one is using. However, I suspect that many people using FL think they using a rigorous technique.

c) Conventional Popperian philosophy of science lays emphasis on statements which empirically falsifiable. The FL set membership functions are not empirically falsifiable, whereas probability statements (even Bayesian subjective probabilities) are capable of refutation with probability 1 - epsilon, for any positive epsilon. Blaise 19:54, 25 Apr 2005 (UTC)

Well, if you think you can improve the article, by all means do so. Just be sure to keep it NPOV. - furrykef (Talk at me) 20:50, 25 Apr 2005 (UTC)

To add my own opinion, I don't think the implementation of fuzzy logic really accomplishes anything that can't be done with other math. I think where fuzzy logic wins is the way you look at a problem. Sometimes a more linguistic approach is more appropriate, and in my opinion, proper fuzzy logic (as opposed to the way it is often applied) is all about being able to phrase a problem and its solution in linguistic terms. Then the solution becomes obvious, and should be easy to implement.

Also, I've been wanting to speak to an "antifuzzy" person for a long time; now that I've met one, I must ask: why was it that the Sendai Subway was (is?) the smoothest subway ride in the world if its use of fuzzy logic is easily replaced by conventional logic? :) - furrykef (Talk at me) 22:34, 25 Apr 2005 (UTC)

>I think where fuzzy logic wins is the way you look at a problem. Sometimes a more linguistic approach is more appropriate, and in my opinion, proper fuzzy logic (as opposed to the way it is often applied) is all about being able to phrase a problem and its solution in linguistic terms. Then the solution becomes obvious, and should be easy to implement.

I can go along with that.

Blaise 11:37, 28 Apr 2005 (UTC)

>why was it that the Sendai Subway was (is?) the smoothest subway ride in the world if its use of fuzzy logic is easily replaced by conventional logic?

I don't think I've ever been that particular subway but, with respect, I'd remind you of the logical fallacy of 'Post Hoc Ergo Propter Hoc' (literally, 'after therefore because) in which one assumes that because event B follows event A one assumes that event A caused event B. In the 1970s an entire issue of Technometrics was devoted to FL. Peter Cheeseman of NASA Ames wrote some good 'antifuzzy' articles. In one, I seem to remember, he showed how you can take any fuzzy controller and replace it with an equivalent probabilistic controller.

Blaise 11:37, 28 Apr 2005 (UTC)

Common misconceptions

This section in particular is the most unacceptably POV piece of promotion in an article that reads rather like a sales pitch. I've not got time in the next few weeks to rewrite it, but I'll put the task on my to-do list. ---- Charles Stewart 04:15, 7 Dec 2004 (UTC)

I agree -- and I'm the one who wrote it! It was kind of meant to be a draft, but, as ends up happening too often, I didn't come back to it. I do think it is true that fuzzy logic is misunderstood and this needs to be noted, but a better job needs to be done of it, yes. - furrykef (Talk at me) 20:02, 7 Dec 2004 (UTC)

I think Blaise's revisions handle the issue well now. - furrykef (Talk at me) 01:59, 29 Apr 2005 (UTC)

This introductory sentence does not make sense.

"Degrees of truth are often confused with probabilities, although they are conceptually distinct, because they need not add up to 100%. "

Totally absent from this sentence is any idea why fuzzy logic might be identified with probability and why they are in actuality different.

A prototype replacement sentence might be: "Degrees of truth are often confused with probabilities: while both deal with "maybes", probability theory deals with the statistical likelihood of the occurrance of an event (hence all probability weightings add up to 100%) whereas degress of truth ..." {fill in the ellipsis at your leisure}.

I'm not an expert in either although I have a fair grounding in probability, so I am reticent to change the article myself. (HTM 2005.04.26 23:50GMT)

Possible bad example of a non-probability truth degree?

With only his little toe in the dining room, we might say Bob is 0.99 "in the kitchen", for instance. No event (like a coin toss) will resolve Bob to being completely "in the kitchen" or "not in the kitchen", as long as he's standing in that doorway.

Wouldn't this 99% degree of truth correspond easily to a probability, namely that the center of a randomly selected particle of Bob's body is within the kitchen? --Damian Yerrick 02:41, 29 Apr 2005 (UTC)

While I don't think that example is particularly good, and your statement is correct, I'd say that example is contrived. Of course nobody would actually think of the problem as, "what percent chance is there of a random particle of Bob's body being within the kitchen"? You could really phrase many if not all statements of fuzzy membership that way. For instance instead of asking if the apple is half-eaten, you might ask, "what percent chance is there of a randomly chosen particle that once made up this apple has passed through somebody's digestive system"? - furrykef (Talk at me) 04:42, 29 Apr 2005 (UTC)

I disagree. This probability-oriented interpretation of fuzzy set membership assumes one particular membership function. Sigmoid fuzzy membership functions, for example, would not fit such an interpretation. -Predictor