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.
Models are inherently lifeless, and quite unlike the inventive independent networks we find in the complex physical world. 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. Assuming that all behavior is deterministic, just waiting for us to find the formula, still lingers. It blocks learning about what we can't write formulas for, though, so I think it should be among the first things to go. Phil Henshaw ¸¸¸¸.·´ ¯ `·.¸¸¸¸ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: [EMAIL PROTECTED] explorations: www.synapse9.com > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Russell Standish > Sent: Wednesday, November 28, 2007 8:11 PM > To: The Friday Morning Applied Complexity Coffee Group > Subject: Re: [FRIAM] FRIAM and causality > > > All scientific models/theories tend to lie on a plane with > the axes "accuracy" and "ease of use". Explicability is also > there, roughly aligned with "ease of use". > > Basically we should only keep those theories/models that lie > on the Pareto front, and discard those that are dominated. > This is why we still keep Newtonian gravity, even though it > is less accurate than GR (ie falsified), but discard the > Ptolomaic system. > > Cheers. > > On Wed, Nov 28, 2007 at 03:42:19PM -0800, Glen E. P. Ropella wrote: > > > > > Anyway, I definitely agree that it's a "mistake" in some sense to > > discard all but the best projections. However, in cases > where a limit > > _exists_ (and it is reasonable to believe it exists), then > it's not a > > mistake at all. Preserving an erroneous model when much > more accurate > > models are at hand would be perverse (or evidence that one > should be a > > historian rather than a scientist). I'm not talking about > the type of > > preservation that allows us to think back and learn from previous > > events. I'm talking about someone _sticking_ to and/or regularly > > relying on a "bad" model even when they know it's wrong. > > > > -- > > -------------------------------------------------------------- > -------------- > 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 > > ============================================================ 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
