On 25/09/2014 22:22, Matt Mahoney via AGI wrote:

1. Intelligence depends on knowledge and computing power. A program
that rewrites itself cannot gain Kolmogorov complexity. Therefore,
self improvement will come from acquiring hardware and learning from
the environment.

One problem with this is that short programs can clearly
produce high Kolmogorov complexity if given enough runtime.
Consider a simple counter. Run it for long enough and it
will count from 1 to:

154998464670145002987498798679541316549415641078895144891513.

This is a sequence with considerable Kolmogorov complexity.

We have compact specifications of intelligence - such as AIXI.
Expanding these short descriptions into practical agents is
possible, but time consuming - due to the need to search a
large search space in order to find them.

A deterministic computer program can indeed gain Kolmogorov
complexity just by running.  The problem is not that this
is impossible, but that it happens slowly.

Another problem is that we don't care about K-complexity -
what we want is agents that can do work for us. Consider
a go program, for example. That could win prizes for us
and lead to fame and fortune.  However, a powerful go
program can be specified with low K-complexity. You just
write a search program to search through possible go
programs until you find one that does very well against
possible opponents (weighted by the size of their source
code).  Here the search program and the halting criterion
are both simple - so this is an example of a valuable
skilled agent that can be specified with low K-complexity.
--
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 |im |yler  http://timtyler.org/  [email protected]  Remove lock to reply.



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