Edward P: II skimmed “LGIST: Learning Generalized Image Schemas for Transfer
Thrust D Architecture Report”, by Carole Beal and Paul Cohen at the USC
Information Sciences Institute. It was one of the PDFs listed on the web
link you sent me (at
http://eksl.isi.edu/files/papers/cohen_2006_1160084799.pdf). It was
interesting and valuable. I found its initial few pages a good statement of
some solid AI ideas. Its idea of splitting states based on entropy is a
good one, one that I have myself have considered as a guide for when and
where in semantic space to split models and how to segment temporal
representations.
Thanks for pointing this out. My v. quick impression is that it is a step,
at least, to a major paradigm shift (although all your criticisms may be
valid). [JWJohnston - I only saw this site literally today after I had
posted]
However - correct me - their "image schemas" are symbolically represented.
They are not true image schemas in my or Lakoff/Mark Johnson's terms.
I believe one of the central sources of the brain's adaptive power is the
ability to represent, manipulate and compare visual and other kinds of
graphics/ "image schemas" directly. IOW it can represent "an agent goes to a
place" as (speaking very roughly):
outline graphics of - a circle or similar (for "agent") - an arrow (for
"goes to") - another circle or square (for "place").
(AFAICT this is consistent with Lakoff & Johnson's thinking).
If I ask you or any human to tell me a story about "an agent going to a
place", you will of course, be able to tell me a virtually infinite number
of stories - a prime example of the brain's adaptive power and ability to
draw analogies.
That ability, I believe, derives from being able to directly, visually
transform a circle or similar into almost any object or creature . Thus you
will be able to tell me a story about a human/man/woman/rabbit/snake etc for
your "agent." That ability can also visually transform an arrow or similar
into any form of object movement - into say a human
running/walking/driving/riding a bus etc. for "goes to" - and can transform
a square into a skyscraper/ town/ shop/ forest etc. for "place."
(One obvious piece of evidence for this is the brain's ability to see any
objects whatsoever their shape as balls on an abacus - it's the foundation
of our ability to count objects and maths).
But all this - as I understand - is beyond digital computers. They can't
handle visual shapes directly - no "imagination." And that is just one of
the absolute brick walls AGI faces, which no amount of tweaking will
overcome.
P.S. I have to say I wasn't that impressed by the other 2 papers of Cohen
linked by JWJohnston. But thanks also for pointing them out
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