Re: Simulating Individual B

[Mike Brown]

I think Paul's question raises two important points - though they may be more
about the organization of science than about the inherent difficulties of
SWARM or any other ABM (Thanks, Chris. I like that acronym better too.)
Ecologists are concerned with aggregations of individuals; they have not had
to know as much about individual species as, for example, zoologists.
Similarly,  microeconomists focus on the behavior of individual firms and
macroeconomists on the aggregate behavior of the economy, etc.

ABM create two problems. First, the ecologist and macroeconomist have to
"ratchet down" and study the behavior of individual entities. Moreover, they
have to know enough about individual behavior to determine which specific
behaviors might be relevant to the question under investigation. While this is
not an insurmountable problem, it does demand a new focus for researchers.

Second, there are some disciplines where data on the behavior of individual
"agents" simply has not been studied. To take a bad example, look at
economics. Macro studies the behavior of the aggregate, and micro the study of
the firm -- but who has been looking at the behavior of the consumer? We have
been able to make a "rational actor" assumption for so long that we have not
bothered to collect data about the real-life behavior of induividual
consumers.

For these reasons, I think Paul is very right -- modeling and validating the
behavior of individual entities can be very tricky. 

Mike
------------------------------
Date: 4/17/97 4:47 AM
To: Brown, Mike
From: address@hidden

Paul Fishwick wrote:

>A key problem with IBM is not that it is necessarily
>computationally prohibitive, but that not enough data are
>available to calibrate the model...

 Paul - why is data calibration more of a problem for IBM
models than for other modelling technologies? What sorts
of problem domains are you particularly concerned about?

 I can allow as how it would be difficult to calibrate
an IBM model of a forest precisely so that each tree-agent
is parameterized via data taken from its respective
real-tree in the forest. Yet, all modelling technologies
make do with some degree of approximation. A reservoir-flow
model of tree-species interaction in a forest would simply
treat all of the trees of each species as "one big tree" 
of that species with respect to some data (such as  concentration, 
nutrient uptake, waste-production, and etc.) while ignoring
other data (such as spatial distribution, variety within the 
species, and etc.) This will be justified for certain questions 
about forest dynamics, but not for others, and might make more 
sense for some problem domains than for others. 

Thus, there is data and there is data. All modeling technologies
must pick and choose among the data, and one always has to 
focus on some reasonable subset of data.  You seem to 
be suggesting that this is fundamentally more of a problem
for IBM models than for other modelling technologies
- can you elaborate?

  ...and, please!, it almost *hurts* to use the acronym IBM!
could we use "ABM" for Agent-Based Models? I think it fits
better anyway, as an agent in this class of models is not 
always an "individual" in the common sense of that term....
I know the term has some historical precedent for models
in this class, but the acronym IBM induces a certain amount 
of, shall we say, cognitive dissonance, no? (not that the 
acronym "ABM" itself is inviolate with respect to prior 
cognitive content....but, still!.....)


Chris Langton


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