How would an AGI choose which things to learn first if given enough
data so that it would have to make a choice? If two AGI's (again-same
hardware, learning programs and controlled environment) were given
the same data would they make different choices?
On Jan 7, 2008, at 11:15 AM, Benjamin Goertzel wrote:
On Jan 7, 2008 12:08 PM, David Butler <[EMAIL PROTECTED]> wrote:
Would two AGI's with the same initial learning program, same
hardware in a
controlled environment (same access to a specific learning base-
something
like an encyclopedia) learn at different rates and excel in
different tasks?
Yes ...
Even in the extreme case of identical external stimuli, two AGI
systems could
evolve slightly differently due to consequences of rounding error.
However, if the AGI systems were built carefully enough (so as not to
be susceptible
to rounding error or other related phenomena) it could be made so that
with totally
identical environments they were totally identical in behavior, so
long as no hardware
failures occurred.
(I note though that minor hardware failures like small defects in RAM
or disk could
always intervene and play the same role as roundoff error, potentially
setting the
two AGIs with identical code and identical environmental stimuli on
different
courses.)
-- Ben
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