On Thu, Dec 06, 2007 at 01:23:00PM -0700, Marcus G. Daniels wrote:
> >
> > And in that
> > sense, even if I can't write a formula for "tying one's shoes", I can
> > still _learn_ how to tie shoes. Further, I can use the inaccurate
> > ("bad") formulas for how to tie one's shoes as a way to actually learn
> > how to tie shoes. Even further, I can _teach_ others how to tie their
> > shoes based on these "bad" models.
> What's the metric you're using for good and bad here? That one person
> looked it up on Wikipedia and another person learned it from their mom,
> i.e. formal vs. informal description? Or ability to stay tied vs. ease
> in shoe removal, or?? Or some mixture of these features? Who decides
> the relative weights for goodness?
>
There is no formalised metric, and it may not even be
formalisable. However, a good model is one that has utility, it can
predict stuff, or explain stuff, or a mixture of the two. A better
model is one that can both explain and predict stuff better than the
other model. Otherwise other models that can better predict or explain
stuff are just other good models.
Obviously there is a certain amount of subjectivity here - some folk
think that a model "God did it" explains stuff, but explaining stuff
in terms of a mysterious, unexplainable, all powerful entity doesn't
work for me, nor for most scientists.
Cheers
--
----------------------------------------------------------------------------
A/Prof Russell Standish Phone 0425 253119 (mobile)
Mathematics
UNSW SYDNEY 2052 [EMAIL PROTECTED]
Australia http://www.hpcoders.com.au
----------------------------------------------------------------------------
============================================================
FRIAM Applied Complexity Group listserv
Meets Fridays 9a-11:30 at cafe at St. John's College
lectures, archives, unsubscribe, maps at http://www.friam.org
