Well, as often occurs with evolutionary learning apps, there is
artistry in creating the fitness function...

This is something we (try to) deal with in NM/OpenCog via using
probabilistic inference to automatically come up with fitness
functions for evolutionary procedure learning

But the Euphoria guys seems to be doing a lot of manual fitness function tuning

ben

On Thu, May 1, 2008 at 5:49 PM, Mike Tintner <[EMAIL PROTECTED]> wrote:
> The link from Lukas seems to suggest that applying this technology is
> something of an art (is that right?):
>
>  "As a side note, the fickle nature of the evolutionary approach is the
> primary reason why euphoria isn't middleware; the team at NaturalMotion
> helps you integrate it. Most often, you have to request behaviors and they
> produce them for you. It takes a lot of experience to be able to capture
> requirements and express them as a fitness function that produces the
> desired results in a way that looks realistic."
>
>  Bob/ Ben Goertzel <[EMAIL PROTECTED]>:
>
>
>
> >
> > >  If you gathered data about how people move in a certain context, using
> > >  motion capture, then you could use their GA/NN stuff to induce a
> > >  program that would generate data similar to the motion-captured data.
> > >
> >
> >
> > A system which could do this generally would be very powerful, and
> > effectively a kind of AGI scientist.  In general terms the problem is
> > one of given the observable data find the most concise model which
> > fits, then use that to make a prediction about future data and try to
> > drive the prediction error to zero.
> >
> >
>
>
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>  agi
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-- 
Ben Goertzel, PhD
CEO, Novamente LLC and Biomind LLC
Director of Research, SIAI
[EMAIL PROTECTED]

"If men cease to believe that they will one day become gods then they
will surely become worms."
-- Henry Miller

-------------------------------------------
agi
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