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Mon Jun 5 16:42:55 EDT 2006


Thank you for your reply.  I think you are right that we probably
would agree about a lot of issues in this area.  Nevertheless, I
still feel the need to caution you about making the strong claim
that there is no real time learning, as defined by evidence of
generalization.

One of the research paradigms used to investigate human category
learning involves first creating a prototype.  Sometimes the
prototype is an image of randomly arranged dots.  Sometimes
it is a collection of related sentences, or an image of
spatially arranged objects. Exemplars of the concept are
then created by applying transformations of various sorts 
to the prototype.  In many cases, the exemplars are created
so that some are relatively close, or similar, to the
prototype, and some are relatively distant, or dissimilar
from the prototype.  An experiment involves training people
to categorize the exemplars, and then after this learning
has occurred, testing them on other exemplars, not seen
before, and on the prototype as well. Since most
psychological experiments are conducted on undergraduates,
in a single one-hour session, many of these category
learning experiments take place within a single hour. 
People usually can perform this task, without being exposed
to the number of stimuli we would expect that a neural net 
would need for such learning, and they can usually
accomplish the learning within an hour (which argues 
against a time-consuming consolidation process being the
responsible mechanism).Hence, I think it would be 
relatively easy to disprove your strong claim, using the
enormous empirical literature psychologists have generated
over the past half-century or so.
 
Nevertheless, I also think it is great that you are making such
a strong claim because it centers attention on the fact that
people are capable of category learning which would seem to be
impossible by our current computational conceptions of learning,
due to high input dimensionality, and the complex mapping functions
they apparently are able to approximate through category learning.
If we can discover how they do this (and I think the psychological
literature provides some clues) we may be able to extend such
capabilities to artificial neural nets.

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