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That is a very important issue (actually you address 2 fundamental issues, in my opinion). I plan to write about them separately in the future.

  1. Simple models versus Complex models. I actually do think that complex models are even worse than simple models. Mainly because: a) complex models are difficult to understand (and I can prove beyond doubt that many simple models have gross mistakes) and b) a bigger parameter space allows for many ways to get a plausible model just by the sheer number of parameters and their ability to touch all solution search space in many ways. So you might get something that resembles reality just by chance that a few parameter combinations actually have the same behavior.

  2. Is modeling any good? Sure it is. I believe simple models are a good supplement to empirical research. Especially to try to find unexpected behaviors which might drive systems and also to try to clarify and rigorously define concepts that field/lab researchers use somewhat "liberally" (in fact one can say that our heads are full of models of reality). But I don't see how modeling can be used to forecast the future or even reconstruct the past.


Of all forms of caution, caution in love is perhaps the most fatal to true happiness - Bertrand Russell
by tiagoantao (put_my_login_here <> gmail com) on Fri Nov 21st, 2008 at 04:56:40 AM EST
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