For neural nets, Daniel Amit had a good book in the 80's reviewing the
dynamics
of attractor neural nets ...

However, it is true that math does not really tell you what you need to know
about
AGI systems ...

Math is more helpful for various sorts of narrow-AI systems, some of which
are useful
as components of AGI systems ...

For instance, Amit discusses the occurrence of strange attractors in ANN's,
but,
there is no science telling us what NN learning algorithms will effectively
cause
the formation of memory-storing strange attractors... the relevant science
doesn't
really go beyond fixed point and periodic attractors...

Similarly, in logic, math tells us a lot about the logic rules, but not much
about how
to create scalable inference control on real-world reasoning problems...

etc.

-- Ben G

On Wed, Oct 8, 2008 at 6:25 PM, Vladimir Nesov <[EMAIL PROTECTED]> wrote:

> On Thu, Oct 9, 2008 at 1:36 AM, Valentina Poletti <[EMAIL PROTECTED]>
> wrote:
> > And here is your first question on AGI.. actually rather on AI. It's not
> so
> > trivial though.
> > Some researchers are telling me that no-one has actually figured out how
> AI
> > algorithms, such as ANNs and genetic algorithms work.. in other words
> there
> > is no mathematical explanation to prove their behavior. I am simply not
> > happy with this answer. I always look for mathematical explanations.
> > Particularly, I am not talking about something as complex as AGI, but
> > something as simple as a multi-layer perceptron. Anybody knows anything
> that
> > contradicts this?
> > Thanks
>
> Read an introductory text on machine learning to get up to speed --
> it's the math of AI, and there's lots of it. Statistics, information
> theory. It's an important perspective from which to look at less well
> understood hacks, to feel the underlying structure.
>
> --
> Vladimir Nesov
> [EMAIL PROTECTED]
> http://causalityrelay.wordpress.com/
>
>
> -------------------------------------------
> agi
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-- 
Ben Goertzel, PhD
CEO, Novamente LLC and Biomind LLC
Director of Research, SIAI
[EMAIL PROTECTED]

"Nothing will ever be attempted if all possible objections must be first
overcome "  - Dr Samuel Johnson



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