Once you read that, I have a further note: The learning, and decision planning 
cycles, comes to equilibrium and you only get a tiny bit more for the same 
compute, so not worth it at some given point, as seen in those metronomes. 
Also, equilibrium may escape pit hole traps if all the cells can signal to each 
other and come to full equilibrium, rather than local. In fact, local may be 
from short term memory focusing, whereas all your memory would need to be used 
to find relations, which is too much compute, so local traps do happen then in 
human brains.
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Artificial General Intelligence List: AGI
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