When the difference between degrees & percentages count
Immortalist
extended to handle the concept of partial truth - truth values between
"completely true" and "completely false". As its name suggests, it is
the logic underlying modes of reasoning which are approximate rather
than exact.
The importance of fuzzy logic derives
from the fact that most modes of human
reasoning and especially common_sense
reasoning are approximate in nature.
Boolean vs. Fuzzy: 300 years B.C., the Greek philosopher, Aristotle
came up with binary logic(0,1), which is now the principle foundation
of Mathematics. It came down to one law: A or not-A, either this or
not this. For example, a typical rose is either red or not red. It
cannot be red and not red. Every statement or sentence is true or
false or has the truth value 1 or 0. This is Aristotle's law of
bivalence and was philosophically correct for over two thousand
years.
Two centuries before Aristotle, Buddha, had the belief which
contradicted the black-and-white world of worlds, which went beyond
the bivalent cocoon and see the world as it is, filled with
contradictions, with things and not things. He stated that a rose,
could be to a certain degree completely red, but at the same time
could also be at a certain degree not red. Meaning that it can be red
and not red at the same time.
Conventional(Boolean) logic states that a glass can be full or not
full of water. However, suppose one were to fill the glass only
halfway. Then the glass can be half-full and half-not-full. Clearly,
this disprove's Aristotle's law of bivalence. This concept of certain
degree or multivalence is the fundamental concept which propelled
Zader Lofti of University Berkely in the 1960's to introduce fuzzy
logic. The essential characteristics of fuzzy logic founded by him are
as follows.
http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol1/sbaa/article1.html
Marshall
> This concept of certain
> degree or multivalence is the fundamental concept which propelled
> Zader Lofti of University Berkely in the 1960's to introduce fuzzy
> logic.
Should be "Lotfi Zadeh."
http://en.wikipedia.org/wiki/Lotfi_Zadeh
He is forever burned in my memory because I was able to
reach him by phone from Honolulu during Christmas of 1984,
and thereby learned I would be getting my CS degree. That,
and the fuzzy logic stuff.
Marshall
alie...@gmail.com
> extended to handle the concept of partial truth - truth values between
> "completely true" and "completely false". As its name suggests, it is
> the logic underlying modes of reasoning which are approximate rather
> than exact.
Personally I find so-called fuzzy logic to be a dead end, and not
particularly relevant to human thought processes. Human thought is
based on multi-weighted neuronal firing patterns, not on "partly"
triggered neurons.
Concepts like "true" and "false" are far too slippery to be
discussed in a physics group anyway. Why _did_ you choose this
particular mix of groups, if I might ask?
> The importance of fuzzy logic derives
> from the fact that most modes of human
> reasoning and especially common_sense
> reasoning are approximate in nature.
Nonsense. They may seem that way to one who never examines their own
thought processes. If they were nobody would ever reach a conclusion.
> Boolean vs. Fuzzy: 300 years B.C., the Greek philosopher, Aristotle
> came up with binary logic(0,1), which is now the principle foundation
> of Mathematics. It came down to one law: A or not-A, either this or
> not this. For example, a typical rose is either red or not red. It
> cannot be red and not red. Every statement or sentence is true or
> false or has the truth value 1 or 0. This is Aristotle's law of
> bivalence and was philosophically correct for over two thousand
> years.
I would have written "useful" rather than "correct", since the
underlying philosophy had no grounding in physics or biology.
> Two centuries before Aristotle, Buddha, had the belief which
> contradicted the black-and-white world of worlds, which went beyond
> the bivalent cocoon and see the world as it is, filled with
> contradictions, with things and not things. He stated that a rose,
> could be to a certain degree completely red, but at the same time
> could also be at a certain degree not red. Meaning that it can be red
> and not red at the same time.
Defining a thing as itself-and-not-itself is a matter of sloppy
definitions.
That wasn't what the Buddha was talking about anyway.
> Conventional(Boolean) logic states that a glass can be full or not
> full of water. However, suppose one were to fill the glass only
> halfway. Then the glass can be half-full and half-not-full. Clearly,
> this disprove's Aristotle's law of bivalence.
Clearly, it disproves nothing. In real-world logic systems, frinst
electronic logic gates, there is a thing called "hysteresis" built in;
if the output of whatever measures the water level follows the level
up from the bottom as it is filled, it will not trip from "less-than-
half" to "more-than-half" until the glass is _more_ than half-full.
Similarly it will not trip from "more-than-half" to "less-than-half"
as the water is drained until the glass is slightly _below_ half-full.
Where the trip points are placed is a matter of definition; place
them so close that there is no clear hysteresis and you get
oscillation, not "fuzzy logic".
It can also be argued from QM that a glass cannot be either half-
full/not-full or even full/empty but always exists in a superposition
of such states.
Clearly, QM violates all philosophy-based human rules of logic, but
I'll take it over logic, conventional or otherwise.
> This concept of certain
> degree or multivalence is the fundamental concept which propelled
> Zader Lofti of University Berkely in the 1960's to introduce fuzzy
> logic. The essential characteristics of fuzzy logic founded by him are
> as follows.
Things are what they are. What we name them only places limits on
what we can do with them.
Mark L. Fergerson
John Stafford
<21ffb812-017a-46fd...@z4g2000prh.googlegroups.com>,
> Personally I find so-called fuzzy logic to be a dead end, and not
> particularly relevant to human thought processes. Human thought is
> based on multi-weighted neuronal firing patterns, not on "partly"
> triggered neurons.
I agree that is true today, but I cannot be certain that it will remain
true as science marches on.
Fuzzy logic is useful in cases where the parameters are well established
and applied only to cases of extremely limited scope. Fuzzy logic has
not (yet) been useful with issues of Natural Language Processing (NLP) -
that effort failed miserably and closed over thirty years ago. (I was an
NLP programmer/researcher). In all, fuzzy logic remains a case where the
user must accommodate the program's fundamental syntactic nature, while
the opposite is what we require.
It is useful in machine talk where a number of inputs are weighed to
cause action (or no action) with input that is not entirely arbitrary,
but within a reasonable scope.
For open cases, consider the famous example of an input: "The man saw a
girl in the park with a telescope."
I have done fuzzy-logic programs, and they are useful but not magic, not
of AI - they are simply a method to deal with situations where the input
is not determinable by earlier inputs.
peguisboy
ZerkonXXXX
> The importance of fuzzy logic derives from the fact that most modes of
> human reasoning and especially common_sense reasoning are approximate
> in nature.
Treating logic and reason as distinct parts is a mistake.
The horror of it all is that human reasoning or sense is not
compartmentalized into neat sets. Logic and reason, however they might be
classified, and 'blind' emotion, however classified, are always in the
same stew of thought. Disciplines can only attempt separation. Language
can only make it seem there is one.
Logic, like language, as applied to computers is metaphor forced back as
literal when comparing it to the human process. As in, 'A car runs faster
than a human'. The great difference between the two 'logics' can be
illustrated in humor, in that most humor is based on logic play or
conflict. A machine will never 'get it' because it never had it.
Speaking of humor...
> Buddha, had the belief which contradicted...
John Stafford
>
> The importance of fuzzy logic derives from the fact that most modes of
> human reasoning and especially common_sense reasoning are approximate
> in nature.
You don't understand what fuzzy logic is. It's a computer science term,
not a psychological term.
alien8er
> In article
> <21ffb812-017a-46fd-8543-f05cd7d93...@z4g2000prh.googlegroups.com>,
>
> > Personally I find so-called fuzzy logic to be a dead end, and not
> > particularly relevant to human thought processes. Human thought is
> > based on multi-weighted neuronal firing patterns, not on "partly"
> > triggered neurons.
>
> I agree that is true today, but I cannot be certain that it will remain
> true as science marches on.
(I suspected the OP had "Artificial Intelligence" in mind and
intended to establish fuzzy logic's credentials as a model for human
thought and by extension as a basis for AI.
I just don't see it.)
> Fuzzy logic is useful in cases where the parameters are well established
> and applied only to cases of extremely limited scope. Fuzzy logic has
> not (yet) been useful with issues of Natural Language Processing (NLP) -
> that effort failed miserably and closed over thirty years ago. (I was an
> NLP programmer/researcher). In all, fuzzy logic remains a case where the
> user must accommodate the program's fundamental syntactic nature, while
> the opposite is what we require.
We've been struggling to reconcile ambiguity and determinism ever
since we identified the concepts, if not before. QM shows some promise
but it's so damn counterintuitive. I'm not sure how I feel about those
who see thought as emergent from QM processes in CSN cyto-microtubules
or other biostructures sufficiently small for QM effects to dominate,
but it would seem to me somewhat more reasonable to try to bend our
thought processes to how the Universe does things than the other way
around.
> It is useful in machine talk where a number of inputs are weighed to
> cause action (or no action) with input that is not entirely arbitrary,
> but within a reasonable scope.
I still see that as a matter of definitions that need refining. But
then all definitions are mutually referential; none are freestanding.
Hence all are arbitrary.
> For open cases, consider the famous example of an input: "The man saw a
> girl in the park with a telescope."
If the person writing the sentence writes it differently, chooses
other words, or uses a language other than English, the ambiguity(ies)
may not be present.
Others may be though; is human language fundamentally ambiguous?
I wrote "language" instead of "thought" because of a phenomenon I
don't know the name for, and since I'm in a philo group I might as
well bring it up.
Ever notice yourself in the process of formulating a sentence? You
know what you're trying to say; you have all the concepts assembled,
but you haven't picked the words yet? There is no ambiguity at that
stage, but when we go to symbolize a thought into a speakable sentence
to share it with another we run the risk of adding ambiguity.
Have you ever tried actually thinking in that mode? It's
frighteningly fast, but the habit of deriving branching implications
quickly quenches it into ordinary "sentence-mode" thinking.
> I have done fuzzy-logic programs, and they are useful but not magic, not
> of AI - they are simply a method to deal with situations where the input
> is not determinable by earlier inputs.
Not quite sure what you mean there; do you mean an ambiguity that is
not resolvable solely in terms of the program's parameters, or not at
all?
Mark L. Fergerson
M Purcell
Ambiguity is inherent simply because everybody is different but
communication is possible through our shared experiences. There are
common definitions for words and usually a common concept among the
different definitions for each word. However if the concept to be
communicated isn't reasoned or structured, it's unlikely it's
communication will be meaningful.