Well, I would look at Ryszard Michalski's work on dynamically interlaced
hierarchies if it was convenient for me to do so. Nothing about this is
mentioned on his home page and the first reference I looked at did not seem
like a breakthrough paper.

I want to finish something that I was thinking about.

We (or a machine) would be able to build strong knowledge if the knowledge
that was gained could be used to reliably predict, explain or produce a
specific outcome.  But often, the outcomes are weak or unreliable
indicators of much of value.  So instead we are left with a lot of weakly
related situation-action-reaction insights that are inexplicably
conditional and variant.

This is a lot like serendipitous learning.  If I try to learn something, I
probably won't be able to figure out what I wanted to figure out (unless it
is something that other people had already figured out and it was within my
field of knowledge).  But I would probably learn something new
serendipitously.  Now can we patch a lot of weak unexpected insights
together?  Yes, but in order to build something reliable out of a lot of
weak structural pieces they have to be integrated pretty thoroughly. The
integration does not have to perfect but the matrix of these things have to
be strong enough to serve as a foundation for greater insights.

Jim Bromer

On Tue, Dec 4, 2012 at 9:31 PM, Piaget Modeler <[email protected]>wrote:

>
> I would agree that you also need mult-strategy reasoning in addition
> to correlations.
>
> Look at Rysard Michalski's work on dynamically interlaced hierarchies.
> He has a fast and efficient mechanism for inference.  He inspired me.
>
> Cheers,
>
> ~PM.
>
>
> ------------------------------
> Date: Tue, 4 Dec 2012 18:36:20 -0500
>
> Subject: Re: [agi] Internal Representation
> From: [email protected]
> To: [email protected]
>
> I discovered something about logic that I never knew before.  It is
> something that I have thought about for 40 years, but I never stopped to
> explore the application.  Now, shouldn't this new insight give me greater
> understanding?  Well, yeah, but it doesn't work that way.  I have a new
> insight but I haven't got any use for it.  So now I have to try to find
> some practical use for it.  Well even though I don't have any use for it, I
> might pick up some street creds by telling other people about it right?
> Well no, not really.  It is really a turn-the-crank kind of thing and the
> fact that I thought about it for so long without ever once examining its
> application is kind of embarrassing.  So now, before I can talk about it I
> have to search for some way to use the idea effectively.  If I found some
> utility for it then I could pick up some credit for it, but until then it
> is just going to make my work with logic more complicated.
>
> The insight was a turn-the-crank kind of insight so it represented the
> application of a familiar idea onto another familiar idea in a way that was
> very familiar to me.  The only thing I did different was to actually see
> how it worked in a few examples.  When I did that I realized that the
> effects were not exactly what I expected.  However, logic is an artificial
> field which is well formed so that other logic-based ideas, like something
> from mathematics, can sometimes be easily integrated into it.  In real
> world examples of ideative projection, the analysis of turn-the-crank
> imagination cannot easily be achieved just by using other (integrated or
> related) methods of internal ideative projection.  And as I just explained,
> simple correlation methods are not an easy substitute for insightful
> methods.
>
> Jim Bromer
>
>
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