Re: Agent complexity

[M. Lang / S. Railsback]

Gary Polhill wrote:
> 
> I'm just trying to canvass some opinions on complexity of agents in
> agent-based models, and I would welcome the views of anyone with a
> moment to spare.... From reading around a little in agent-based

I guess our models fall under the "fewer rules is better" philosophy,
trying to find rules that are (conceptually, if not computationally)
simple yet cause a wide range of realistic behaviors to emerge. 

One reason for this approach is that we are simulating agents (fish)
whose sophistication is probably more limited than a persons and
certainly harder to study. We can't test our models by seeing if they
reproduce things like language, goals, and economic structure of trout.
So if instead we can find simple rules that explain a wide range of
trout behaviors, we think we've learned something about trout, as well
as complex systems. 

We've had success with an approach* based on fitness maximization, where
fitness is defined as the expected probability of survival over a future
time horizon. Telling fish to make decisions simply by maximizing their
expected probability of surviving (and growing big enough to reproduce)
over the next 90 days causes them to do a bunch of realistic reponses to
various changes in their situation (research just submitted for
publication). 

This approach is really just microeconomics for fish, so I'd bet it
could apply to some models of people.

Steve

*Railsback, S. F., R. H. Lamberson, B. C. Harvey, and W. E. Duffy.
Movement Rules for Spatially Explicit Individual-based Models of Stream
Fish. Ecological Modelling 123: 73-89, 1999.
-- 
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707-822-0453; Fax 822-1868


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