Replying to LO28473 --
knowledge falls into two categories known and unknown. That which is known
does not need to learned. that which is unknown become known through
experience. This experience we call learning. it is an active process. One
can experience something and not learn anything because learning requires
language enables knowledge transfer. knowledge transfer makes for more
thus learning applies only to unknown. Once learned that knowledge can be
encoded. assuming of course one has the appropiate encoding method.
now the correspondence between language and the experience is not exact,
since language is an abstraction and thus details will always be left out
in the encoding process. so the translation of an abstraction into reality
requires an iterative process for all the details to be included.
Entropy is a measure of disorder within a system. system here presumes an
open system with a permeable boundary.
Being a measure of disorder, it is also a measure of order within a
system. Let us call that which is known order and that which is unknown
entropy for this system the conversion of that which is unknown to that
which is known by the process of intentional experience or learning.
E (entropy) = known - Unknown. where E is always < 0. or 1 or some fixed
However this is for open systems.
For closed systems E = 0 since that which is unknown becomes known there
is nothing more to learn.
an example of a closed system is the game tic tac toe.
an example of an open system is an ecology. a solar system , a galaxy.
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