> 
> Brad wrote:
> > I think this is a core principle of AGI design and that a system that
> > only makes inferences it *knows* are correct would be fairly
> > uninteresting and incapable of performing in the real world.  The fact
> > that the information in the P(xi|xj) list is very incomplete is what
> > makes the problem interesting.
> > 
> > Or maybe I'm misinterpreting your intent.
> >
> I agree perfectly with your "core principle", and my proposal was not to
> only make inferences that you know are correct. I think you may be
> misinterpreting: lets say that we know P(Xi), and want to guess at P(Xi|Xj).
> We have insufficient knowledge, so we need to make some assumptions to
> approximate P(Xi|Xj).  I argue that under these circumstances, the best
> assumption to make is that Xi and Xj are independent, (ie, P(Xi|Xj)=P(Xi)). 
> Does this clarify things?


You are basically saying, for each unknown P(Xi|Xj), assume it equals P(Xi).  

I think this conservative approach, while well grounded in rationality, doesn't really 
allow for the existence of useful and interesting inference.   An AGI has to tolerate, 
and work with, large degrees of uncertainty.  This includes assuming dependencies 
without sufficient evidence.  I can say that in the biological sciences, one has to do 
this constantly.  What separates the good scientists from the not-so-good is an 
ability to keep track of many low-confidence assumptions simultaneously, shake them up 
and see what theories fall out that violate the fewest of them.   

-Brad




> 
> Moshe
> 
> > 
> > 
> > -Brad
> > 
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