Intelligent ways to search parameter space?

[Ken Gosier]

So, I've been working a while now on making an extension to the ASM
model for the stock market. I've extended it to many assets, and 2 types
of agents.

I've got it up and running, which is very cool, and I have the
LispArchiver hooked in, so it's nice and easy to make different runs for
different parameters. I don't yet have a batch mode, but I can figure
that out as well.

At this point my main task is to start searching parameter space, to
find interesting behavior. But: there are ~50 parameters to this model,
so exhaustively searching through parameter space in a brute force way
is not feasible. Granted, there are only about 5-10 params that I
initially care about messing around with, but still it's a daunting
task.

My question is: are there reference materials out there, which provide
some guide to intelligently searching parameter space? I was wondering
if there's been any work saying something like: These are general
qualities of different types of complex systems. To produce these
qualitatively different types of behavior, then you should follow this
strategy in setting up the model and/or parameters.

I've already managed to change the behavior of the model from completely
unstable, to mostly stable, just by using financial knowledge to set the
parameters realistically.

Apologies if this question is overly vague. I know there's lots of good
materials out there. (I know the Michigan Complex Systems page has a
good readings page about complex systems.) But, if someone knows some
materials in this specific area, it would be quite helpful. Many
thanks--

Ken Gosier
address@hidden
address@hidden


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