Thus spake Jochen Fromm circa 01/01/09 07:05 AM:
> I wonder if we can find fundamental agent-based models which define a
> certain area or subfield and explain abstract terms of fundamental
> importance (like 'power' or 'culture')
I think such an attempt will necessarily devolve into a discussion of
how "agent-based modeling" is different from (if at all) other methods
for exploring the world (e.g. continuum math). FRIAM's beaten around
that bush a couple of times since I've been subscribed and it hasn't
really gone anywhere. In my opinion, combinatoric methods like ABM are
no different from any other form of math. But others on this list
insist that ABMs are not mathematics. Still others see a large
distinction between math (method) and science (knowledge), where I see
them as so deeply intertwined that the distinction is false (but useful).
But we can be good computationalists/deists and set up the
discussion/simulation, watch it play out, and draw our conclusions
post-execution. [grin] Marcus and Owen have already gotten us started with:
1) transformation with variation (e.g. gillespie algorithm)
2) estimation (i.e. optimization with variation), and
3) teleological ("anticipatory") deduction (e.g. game theory)
My guess is that variation and teleology are absolutely necessary for
describing complex systems, especially like we find in biology. Biology
is the _middle_ of science. As we go "down" (finer grain) to physics,
variation and teleology begin to disappear (until we get to entanglement
anyway). I also suspect that as we go "up", variation and teleology
disappear. (Personally, I believe the cause of the disappearance is the
abstraction required and available when you go "down" or "up".
Abstraction mitigates against variation and teleology.)
The domain of biology is huge and I think social systems, wherein we use
words like "power" and "culture", are well within it and, hence, my
guess would be that variation and teleology are necessary (though
perhaps not _true_).
So, the task is to further slice up the classification so that each
method can be evaluated in the context of a domain as, say, "very useful
in that domain", "useful", "not very useful". (If you don't like the
categories (1-3) above, then come up with some others. You can also
replace "useful" with "common".) I suspect when/if we got to a
classification granularity of 5-9 (possibly falsely) distinct methods,
we can begin to assert where each method is _most_ useful.
And where a method is most useful and other methods are least useful,
then we can say that that most useful method is "fundamental" to that
domain.
--
glen e. p. ropella, 971-222-9095, http://agent-based-modeling.com
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