On Wed, Dec 2, 2015 at 5:36 PM, Jim Bromer <[email protected]> wrote:

> Ben, Your reply about the makes sense but you should have somehow made it
> clearer that you were making your choices based on some subjective reasons.
> I do not think that Solomonoff's methods can be used as a basis for AI and
> there is no way that you can demonstrate that it has been. Bayesian
> methods, on the other hand, have been demonstrated to be reasonable basis
> for AI. If I was spending the time to write an article like that I would be
> able to provide some substantial basis defending my point of view.
>

I could provide a "substantial basis" underlying  the choices I made in
that article, but the nature of such an article is that it has to be brief
and can't contain the justification underlying each point mentioned...

Regarding Solomonoff induction, it's the conceptual basis underlying any
work done in machine learning that uses a simplicity bias (e.g. MOSES with
an Occam bias ... any Minimum Description Length work, etc.).   I don't
think it's the golden path to AGI but it's certainly relevant.   The
relatively substantial amount of space devoted to the topic in that
Scholarpedia article is somewhat correlated with the preferences of the
article's referees, though, to be honest ;p ...

-- Ben



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