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.


-- 

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A/Prof Russell Standish                  Phone 0425 253119 (mobile)
Mathematics                              
UNSW SYDNEY 2052                         [EMAIL PROTECTED]
Australia                                http://www.hpcoders.com.au
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