If you give yourself infinite computation power an exponential brute force
search of physics engine logic, contains all methods that exist in the
environment, as long as it only involved still objects, which were simulated
correctly, according to some primary mover. I was wonder if taking it from
this aspect it might be able to help you work out what its sub movers it would
develop would be. A fairly average example would be make it to situational
topology b, from its current situational topology. A full power search,
ubersampling physics engine code, would go through every possible permutation
of spacial modifications. This setup, would automatically contain all
possible manipulations of static lifeless objects, all methods, so if you
were to not do this, and form the methods instead - it should come up with the
sub-goal relationships that end it up in the exact same decision as if it were
actually supersearched, but its not allowed to leap straight to it, it has to
learn all the physics based concepts from the ground up, start to finish,
building up on itself exactly. Sorry for being a let down I cant think of
it still. XD
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Artificial General Intelligence List: AGI
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