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Fuzzy Logic

en.wikipedia.org

21–30 of 43 posts

Re: Fuzzy Logic

#22
Since we're talking about non-classical logics, I also like modal logic, which deals with uncertainty too, but in a very different way. Here, facts / assertions are not associated with a numeric value, but with a modality, a symbol, meaning "it is possible that F is true", "it is not necessary that F is true", "F is usually true", "F was true yesterday", or "I know I don't know whether F is true or false".

https://en.wikipedia.org/wiki/Modal_logic

It has interesting properties, and it avoids the main pitfal of fuzzy logic IMO: when a fact is associated with a truth value of 0.8, what does that really mean? Why is the truth value 0.8 rather than 0.81, for instance? Can we say so for sure?

Re: Fuzzy Logic

#24
post #8

"Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false." Can someone explain how this is different than bayesian statistics?

Bayesian statistics has to follow Bayes rule. There is a fairly specific framework behind the numbers in Bayes (i.e. probability). Fuzzy logic is looser. You could say Bayesian statistics is a subset of Fuzzy logic. Given how informal people have to be in Bayesian statistics to come up with reasonable priors (e.g. uniform), and how well it works by just guessing reasonable values, it could be argued that the power of…

> You could say Bayesian statistics is a subset of Fuzzy logic.

I don't think that's accurate. Concepts like conditional probability and independence have no analogue in fuzzy logic.

Re: Fuzzy Logic

#25
post #8

"Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false." Can someone explain how this is different than bayesian statistics?

As far as I can tell... Bayesian statistics is a model of the real world, fuzzy logic is just an easy to compute, bad approximation of reality that assumes everything is independent. (Someone correct me if I’m wrong; I’ve only studied logic and Bayesian stuff, not fuzzy logic)

Re: Fuzzy Logic

#27
post #8

"Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false." Can someone explain how this is different than bayesian statistics?

Did you wake up early this morning? Can you always answer that by a clear yes or no? When do you draw the limit between them? At 7:30? So if you woke up at 7:29:59 you would answer Yes and later No. Instead you could put a distribution (but NOT a probability distribution) for belonging in the set of early that would look something like this. If you wake up before 6:30 it would definitely 100% be early and at 8:30 it…

It's better to think of fuzzy logic like correlation in quantum superposition. As opposed to probability which is a different concept that maps to Bayesian logic.

Does not make it much easier to understand? You bet, which is why symbolic logic is much more useful.

Re: Fuzzy Logic

#29
post #17
post #16

Earlier quoted context omitted.

Apart from the other answers, there is also one important technical difference. Fuzzy logic is truth functional but probability is not. That is, in fuzzy logic, if you know the fuzzy truth value of A and of B, you can calculate the fuzzy truth value of “A and B” “A or B” and so on. Not in probability. If you know, let’s say, A and B both have probably 0.9, you don’t know enough to calculate the probability of “A and…

Yeah but in the real world it doesn't matter does it? you cannot compute the probability A and B for a reason: they might be related (what if they're mutually exclusive for instance? ) So how does fuzzy logic deals with this?

> So how does fuzzy logic deals with this?

It doesn't, because truth values are not probabilities. They are answers to questions more like “How tall is X” than “How likely is it that X is sufficiently tall”.

Re: Fuzzy Logic

#30
post #14

Back in the 90s when neural networks and fuzzy logic were the rage and were going to solve all problems of human mankind (déjà vu?), I stumbled upon this nice course put together by Texas A&M in the form of an "ebook" (aka Win3.1 application). Lofti Zadeh himself was a contributor. I looked it up in my bookmarks and I cannot believe that the site is still up: http://faculty.petra.ac.id/resmana/private/fuzzy I was ver…

Out of curiosity i downloaded and downloaded the tutorial and it looks to be more of a hyperlinked multimedia(ish) application, similar to something you'd see made in Hypercard (which makes sense since it seems to be made in ToolBook which essentially was a Hypercard clone for Windows 3.1) and less of something like a PDF, something you'd see in an Amazon Kindle or something you'd see as an EPUB (which is what i think most people would associate with ebooks nowadays).

I made a quick capture under VBox with Windows 3.1 for others to see, (though i think it should also work under Wine and otya128's winevdm port to Windows 10):

http://runtimeterror.com/pages/badsector/nyan/gimme/webm/fuz...

EDIT: i started reading it now for real and i have to say it is a very interesting way to teach. In theory the hyperlinked approach would work fine in the web, but i cannot think of anything similar in practice. The closest i can think of was some interactive examples in a blog post i found some years ago about making a 2D game.

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