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experiment presented in this paper
is intended to show the theoretical
possibility of certain kinds of `self-referential' weight matrices.
The network I have described can, besides
learning to solve problems posed by the environment,
also use its own weights as input data and can (in principle)
learn new algorithms for
modifying its weights in response to the environmental input and
evaluations. This effectively embeds
a chain of `meta-networks'
and `meta-meta-...-networks' into the network itself.
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