>It will be really nice to watch as they make progress trying to understand
>the brain, with its 10^12 neurons and 1000 connections for each (more or
>less). But at this point I would really like to understand what's happening
>in some very well-defined and relatively simple 1000-class ontologies when
>they do some reasoning. Looking at a 50-step proof with dozens of obscurely
>labeled Skolem constants (such as Vampire generates) and trying to follow
>the reasoning is enough challenge for me now. (01)
Indeed. Which raises an interesting point. Skolem
functions arise from AE sentences, which (as we
were recently reminded) can be re-written using
functions in the first place. If they are written
that way, then those functions can be given much
more intuitive explanatory names. For (a toy)
example, if we say that every man has a father by
writing (02)
(forall ((x man))(exists ((y man))(Parent y x))) (03)
then this will be Skolemized to something like (04)
(forall ((x man))(Parent (skolem4571 x) x)) (05)
whereas if we had used a function in the first place, we might have (06)
(forall ((x man))(Parent (fatherOf x) x)) (07)
as our axiom. (08)
All of which suggests to me that any KR system
that has to resort to Skolemization is not
providing the proper engineering support for good
ontology construction. (09)
Comments? (010)
PatH (011)
>
>Pat
>
>Patrick Cassidy
>MICRA, Inc.
>908-561-3416
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>
>> -----Original Message-----
>> From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-
>> bounces@xxxxxxxxxxxxxxxx] On Behalf Of Jerry Hobbs
>> Sent: Monday, December 17, 2007 7:27 PM
>> To: [ontolog-forum]
>> Subject: Re: [ontolog-forum] brainwaves (WAS: to concept or not to
>> concept, is this a question?)
>>
>> When I reviewed what was known about the brain in 1990, I came to the
>> conclusion that it was as if we asked what happened at the SuperBowl,
>> and we were told it took place in Florida and here's how you throw a
>> forward pass.
>>
>> When I looked again in 2000, we could now be told it took place
>> in Miami.
>>
>> Today we're standing outside the stadium and hearing the cheering,
>> trying to guess the course of the game from that.
>>
>> -- Jerry
>>
>> -------------------------------------------------------------------
>>
>> Deborah and Randall,
>>
>> I just want to emphasize that points that Randall made
>> and to add the comment that neuroscientists themselves
>> are the first to admit three very important points:
>>
>> 1. An enormous amount has been learned about the brain
>> during the past 30 years. Many of the experiments
>> show in detail which parts of the brain and even
>> which individual neurons become active during some
>> kinds of mental processes.
>>
>> 2. But the more they learn, they discover much, much more
>> that remains completely unknown. In particular, knowing
>> what parts become active, does not tell us anything about
>> what those parts are doing.
>>
>> 3. Many published reports that show how computers "can read
>> the mind" merely show that it is possible to find correlations
>> between certain mental activities and activity in certain
>> parts of the brain. Finding such activity can be a useful
>> clue to what the person is thinking. But such clues are
>> similar to what a sensitive person can detect by looking
>> at facial expressions, tone of voice, gestures, etc.
>> All of them are clues, but they don't tell us what is
>> actually happening in the brain.
>>
>> RRS> Keep in mind that LTP is only one aspect of long-term
>> > information storage in neuron networks. The topology of
>> > connections matters, too, obviously. There's probably other
>> > stuff I'm unaware of or am not thinking of right now.
>>
>> Some of that other stuff includes the internal structural
>> and chemical organization of each individual neuron. The
> > so-called neural networks treat neurons as very simple
>> switches, and AI systems have obtained some interesting
>> results from combinations of such switches -- but that
>> does not imply that those switches are simulating
>> actual neurons.
>>
>> Neuroscientists believe that each neuron is far more complex
>> than a simple switch. A better model might be a rather
>> complex computer chip or even a complete computer in itself.
>> But nobody knows what kind of computer it might be or what
>> kind of code or storage it is processing internally. Even
>> though researchers can detect the external firing patterns,
>> nobody has been able to decode those patterns and determine
>> what kinds of messages they are sending or receiving.
>>
>> In summary, there's going to be much more information coming
>> in the next 30 years, but nobody knows when it would be
>> possible to get a complete simulation of a single neuron,
>> let alone the complete brain of a fruit fly. Don't even
>> think of holding your breath waiting for a simulation
>> of a complete mouse brain.
>>
>> John Sowa
>>
>>
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