Tuesday, May 4, 2010

Bottom-Up AI

A recent commenter (yes, people do comment here, on occasion) said that building AI from the bottom up is the only way to go.  I spent some time thinking about that, and I have to agree.  Then I started expanding my thinking to include all artificial complex adaptive systems (ACAS).  If I wanted to build an ACAS, I would HAVE to start from the bottom, then test from the top down. 

This sounds like an axiomic system.  Create a set of axioms (building blocks) and see if you can reach a set of higher-level principles with those axioms.  If not, you might have bad axioms, bad operators to use on those axioms, or just a bad goal in general.  Even reaching the principle might not prove anything, for the same reasons.

The downside (the only one I can see so far) is Godel's Incompleteness Theorem.  The mind is self-referential.  Godel shows use that axiomic systems run into problems when they become self-referential.

Overall, this sounds like a promising avenue to explore.  Can any complex adaptive system be translated into an axiomic system?  If so, how does Godel come into play?  Is it even relevant?

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