Sadly, this is work I struggled with and completed many years ago. It has been 
suffering from NIH syndrome. Hotshots would rather spend years trying to 
reinvent the wheel. In my opinion, a most unscientific approach. But I'm 
getting old now. With every passing year I seem to care less and less about it.

Maybe grok these few statements. I'm not going to go into explaining it here:
>The associative links are de-facto weighted, but not in a linear fashion. 
>There's more than one metric at play, as well the factor of relativity.
>Furthermore, once the graph/model (representative form) is mature (there are 
>rules for this state of existence), 2 control factors come into play as well, 
>which indirectly affect these weights and the sums of the respective, 
>subsystemic totals.

NOTE: Bearing in mind, this is an attempt to deal with a scalable, stochastic 
CAS at complexity levels 10-15+, not systems with less complexity (<and =10), 
as systems with higher levels of predictability.

________________________________
From: Jim Bromer <[email protected]>
Sent: Thursday, 21 October 2021 01:18
To: AGI <[email protected]>
Subject: [agi] Re: Ideas Have to Act on Other Kinds of Ideas

I guess an interpretable network of (graph) components (or subcomponents) that 
uses hypergraphs to refer to them could work in the way I am thinking. To use 
them in a variety of what-if scenarios the lines as well as the nodes could be 
varied. But I think this would still be in the Relevancy Problem (so to speak). 
 Maybe the lines do not need to hold values (weights) but then some 
associations would have to noted in hypergraph formulas. You want the program 
to try different weights of the associative links as well as the nodes. But 
this is hyper-complex (if you'll excuse the pun).
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