Biting my lip over here. [Don't respond...DON'T RESPOND!]

-- 
Doug Roberts, RTI International
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On Dec 5, 2007 5:14 PM, Russell Standish <[EMAIL PROTECTED]> wrote:

> This is a very "Phil Henshaw" response - its a bit hard to know how to
> respond to this.
>
> On Thu, Nov 29, 2007 at 10:14:41AM -0500, Phil Henshaw wrote:
> > Russell,
> > That's a sound way to choose the most valuable model of the moment, but
> > it won't help you with what models can't show.   You need to study the
> > space between the models.  If you use optimal models and study the
> > discrepancy between them and the continually changing systems they
> > imperfectly reflect, you have a chance of seeing and engaging with the
> > real thing.
> >
>
> So you're just saying we should be performing crossover operations
> between successful models? But this is exactly what happens when
> multidisciplinary teams form leading to cross-polination of ideas. The
> results are often quite interesting and advance the field.
>
> > Models are inherently lifeless, and quite unlike the inventive
> > independent networks we find in the complex physical world.
>
> As a long time ALife practitioner, I don't really believe this at
> all. I have often been surprised at the behaviour of my models, even
> lifelike behaviour.
>
> > Using the
> > 'best' model to represent nature is like putting a high resolution
> > picture of a frog in your son's terrarium.  Very nice, but not the real
> > thing.
>
> Nice metaphor, but I don't understand how it relates... What about
> replacing the frog with a detailed robotic imitation that has been
> evolved to imitate frog behaviour using artificial life techniques?
>
> > Assuming that all behavior is deterministic, just waiting for us
> > to find the formula, still lingers.
>
> What do you think of stochastic descriptions of nature then (starting with
> Boltzmann's statistical physics)?
>
> > It blocks learning about what we
> > can't write formulas for, though, so I think it should be among the
> > first things to go.
> >
>
> What we cannot "write formulas for" (by which I mean "find
> compressible descriptions for"), we cannot learn. For that is the very
> nature of learning - being able to generalise from the specific.
>
>
> --
>
>
> ----------------------------------------------------------------------------
> A/Prof Russell Standish                  Phone 0425 253119 (mobile)
> Mathematics
> UNSW SYDNEY 2052                         [EMAIL PROTECTED]
> Australia                                http://www.hpcoders.com.au
>
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>
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