[FRIAM] The art of agent-based modeling
Marcus G. Daniels
mgd at santafe.edu
Mon Aug 14 10:07:05 EDT 2006
Jochen,
> -If the simulation is too complex and matches
> official experimental data, everything takes a
> lot amount of time (creation, setup and execution of
> the experiment and finally the cumbersome analysis
> of the complex outcomes), and it becomes increasingly
> difficult to identify the principal laws, because it is
> easy to get lost in the data or bogged down in details
>
This may be a false choice. In the case of having some data of
moderate resolution, there's no point in making a hugely elaborate model
and simulation, because you'll never be able to validate beyond your
data anyway. And if you don't validate, although the modeling still
may be useful as an thought experiment, it isn't science. You have to
be able to say something that can be shown to be wrong. If you do aim
to learn things about the world and then predict them it's not desirable
to have giant black box with lots of moving parts. It's better, if at
all possible, to have a simple story and make the simulation nothing
more than apparatus to help extend the data so that the dynamics can be
studied by theoreticians.
Another mode of use for ABMs is to lower expectations of theoretical
traction and opportunistically look for ways a model makes useful
predictions and then modify the model in that direction over time.
This is a risky and expensive craft, but one that might have high enough
payoffs to consider (e.g. national security).
It depends on the data and what is of interest. If the data tells you
about a number of rare events, and it is these events is what you really
care about, then it may make sense to loosely model everyday behaviors
and focus on model microstructure that can create the rare events you
care about.
Finally, sometimes microstructure is known with clearly defined degrees
of freedom, and the dynamics are of interest. Consider modeling a
factory where different assembly regimes are to be evaluated.. There's
no need to validate here because the whole exercise is to answer
what-ifs about realizable specific systems.
Marcus
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