You can also evolve atomese programs maximizing some fitness, like MOSES
does, you don't necessarily need experience. MOSES is gonna be ported to
the AtomSpace, it sounds related to what you want to do.
Nil
On 10/04/2017 07:48 AM, Linas Vepstas wrote:
Learning requires a bunch of experiences from which to generalize, and
some way of deciding if the thing that was learned is worth remembering.
Oh, and then using what you've learned. You might enjoy debating on the
AGI mailing list, to discuss how this might be achieved.
--linas
On Wed, Oct 4, 2017 at 10:54 AM, Daniel Fagerlie
<[email protected] <mailto:[email protected]>> wrote:
I just had a passing thought, and I wanted to see how others have
done something similar; what it is called?
I may not understand the atomspace fully. If so, forgive my blunder.
Also, I'm no expert on these subjects, which is about to be obvious,
but I decided to make this post anyways for the experience.
My thought is to grow a certain number of atoms within an atomspace
using a genetic algorithm approach, but track the change from
chaotic atomspace to the ordered atomspace. The problems that the
simple mind is to solve should be something interesting but small
enough to be properly evolved within a reasonable time frame (I'd
have to give this more thought, but maybe an environment where logic
is needed, not just action/reaction). The idea is to study the
process of how genetic learning happens in the context of opencog,
and how it relates to the current work in creating mind agents for
learning.
Maybe this has already been done, or it's a concept hatched before I
have sufficiently gained understanding. Anyways, there it is.
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