Talking on a very abstract level, MOSES could be ultimately developed
so that it explores what you could call "constraint relaxation
strategies"; combo trees are built such that they meet the constraints
"optimally" with more-or-less random exploration of different
trade-offs. Pure MOSES (current) starts with no knowledge and learns
along the way, you could also call the knowledge learned
"constraints", especially once it would be expressed in
"transfer-friendly" declarative way.

"Everything is a constraint."

On Wed, Dec 17, 2008 at 4:23 PM, Ed Porter <[email protected]> wrote:
>
> My point was the parallel constraint relaxation would appear able to be used
> much like a genetic algorithm, except that in a Novamente system it would
> have the ability to take advantage of much of the relevant world knowledge,
> and knowledge about how to best reason from world knowledge, that was
> contained in hypergraph, when proposing solutions.
>
>
>
> Your acknowledgement that in WebMind the hypergraph was used without MOSES,
> implies you agreement that the hypergraph could be used for exploring a
> possible solution space to various problems, and doing creative thinking.
>
>
>
> My REAL main point, was that from my reading about Combo and MOSES in your
> 2007 Novamente book, and from reading one of Moshe's long papers about it,
> MOSES seem to take to little advantage of all the rich, complex hierarchical
> and generalization knowledge contained in the hypergraph --- although it was
> clear to me that their would be ways in which it could be modified to do
> so.
>
>


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agi
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