But the bottom line problem for using FOPC (or whatever) to represent the
world is not that it's computationally incapable of it -- it's Turing
complete, after all -- but that it's seductively easy to write propositions
with symbols that are English words and fool yourself into thinking you've
accomplished representation. A real working logic-based system that did what
it needed to would consist mostly of predicates like
fmult(num(characteristic(Sign1,Bit11,Bit12,...),mantissa(Bitm11,Bitm12,...)),
num(characteristic(Sign2,Bit21,Bit22,...),mantissa(Bitm21,Bitm22,...)),
num(characteristic(Sign3,Bit31,Bit32,...),mantissa(Bitm31,Bitm32,...)))
:- ... .
And it would wind up doing what my scheme would, e.g. projecting the
n-dimensional trajectory of the chipmunk's gait and the leaf's flutter into a
reduced space, doing a Fourier transform on them, and noting that there was a
region in frequency space where the clusters induced by the two phenomena
overlapped.
Josh
Josh,
I totally agree that numeric representations are more natural and more
efficient for perceptual data
processing.
One of my questions regarding your approach is why you think that
similar numeric representations are also natural
and efficient for more abstracts sorts of data processing.
An alternate view would be that the kind of processing you're describing
is more in the vein of "perceptual
preprocessing" rather than constituting the crux of cognition...
-- Ben
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