But I should clarify-- I don't mean the final routines are explicitly
coded in exactly. The genomic code runs, interacts with data in
the sensory stream, and produces the mental structures reflecting
the routines. That's how it evolves, because as the genome is being
mutated, what survives is what works in development which takes place
in contact with the sensory stream. If the
monkey doesn't see the other monkey shrieking, it won't build the
snake fear routine. There will thus be a sense in which what is
genomically coded is a bias to develop routines, rather than explicit
routines in final form.
Agreed, yes. This is the main point Elman et al make in their book as
well, as you know.
But as I try to think what kinds of bias I can
write down that will be useful, and what kinds accord with
introspection, big chunks of code like scaffolds come to mind.
This is where I'm not sure you're right ... I'm not sure the relevant
biases are best provided
to an AGI system as "big chunks of code."
For each of your big chunks of code, I might be able to figure out a way
to achieve the same
bias -- in a more flexible and learning-friendly way -- via subtler
mechanisms within the
Novamente system (a few parameter tweaks, a few small in-built
procedures, etc.)
-- Ben
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