Fuzzy logic has inspired the most mathematic journals of any math derivative. However, it's largely ignored in schools. There is a mathematical proof that fuzzy logic is a superset of probability, which you take in high school, and there have been numerous examples of the principles in this math being able to do things that traditional expert systems or probabalistic systems can't handle.
So why is fuzzy logic ignored? Is it because of the name? Interestingly enough, there are tons of scientists who study & use this, and it's taught in schools...just not in the US, but in China & Japan.
...arachnid, they could teach it the same way they teach probability.
Example:
I learned in high school that the probability of rolling a 1 on a six sided dice was 1/6. If you throw the dice and times, it's still 1/6 - eg, the probability is the same, irregardless of the historical occurences of 1 through six.
Then I learned about mean, mode, average, and so on - all to deal with some "specialized instances" of calculating things which had I not gotten into business many of these things would have been useless by & large (aside from future math classes).
Now consider fuzzy logic, at it's most basic: Jack is taller than John, even though they are both "tall". Bill is 6'2, Jim is 6'1, and Bob is 6' even.
Now, if the definition of tall is 6'1 and above, isn't it useful to know that you'd still group them all in the same bucket, even though one doesn't fit the definition?
Eg, when people describe things, it's more like fuzzy logic than it is like probability.
Another example: Suppose you develop a system to check for temperature change in a factory, because if the system gets too hot too fast, it melts down. So you'd have to constantly check (in one way) for the temperature, and then be sure ti's below a certain level (binary check / yes or no).
Then, consider building in a "fuzzy controller": As the temperature fluctuates, if if fluctutes more than "normal", you start implementing the "cooling process" faster than normal, to account for the rapid rise. What is rapid? Well, it's simply "faster than normal"...
Sure, it's an oversimplified explanation of a fuzzy control system like they use in manufacturing, BUT, if you explain the process and the potential savings (big) of doing things this way...well, that's applicable to real world. Where as my lessons in probability & gambling (which they were) in high school math class weren't applicable in real world situations, unless I took up gambling :)
Steve - fuzzy logic was invented in the 1960's...;) so it's 40 years old, and actually, older than many of the educational theories they use, today, to educate my kids in 1st & 2nd grade than those techniques I learned in the 80's when I was in those grade levels...so, really, it's more "classic" than the education they're getting today, eg, not new.
The difference between stats as it's taught in high school and "fuzzy logic" is application. There's not much you can apply fuzzy logic to outside machine learning and (possibly) industrial control systems as you describe. Stats, on the other hand, has extremely broad application.
Unless I gravely mistake what you mean by "fuzzy logic", it's not really applicable outside specialised university papers. It's a fairly specialised statistical/machine-learning technique.
I dont get it, whats fuzzy logic? In my defence, I am a scientist, not a mathmatician!!
