My idea of judgment does rely on reason based reasoning.  This
definition would seem to favor explicit representation.  However, I do
recognize that we make some decisions that are not based on explicit
reasons so I do include implicit or hidden reasons in my definition of
judgment.  And the fact that we can use poor judgment or poor reasons
for making a decision does seem to weaken the theory.  But by making
AGI learning partially dependent on previous judgment-mediated
learning, the idea does hold together even if it cannot be pinned down
to an absolute computational definition.

How does this idea of judgment-mediated-learning tie into a definition
of an AGI function that can be differentiated from a Narrow AI
function?  My idea of conceptual typing, dynamic creative and rational
creative functions and trial and error methods can be combined to
explain how novel conceptual typing might be developed as the program
is running.  So that means that I have an explicit way of dynamically
developing new ways of looking at the data as the program is running.
In most contemporary AGI models this is not detailed.  So, artificial
judgment can examine the presumptions behind the conceptual structures
that are running as well as develop results that are dependent on
them. - Jim Bromer


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AGI
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