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Re: Simulating Individual Behavior


From: Doug Donalson;
Subject: Re: Simulating Individual Behavior
Date: Thu, 17 Apr 1997 15:14:03 -0700 (PDT)

Be careful of this method.  There are at least two
main problems you can run into.  The first is that you can
force fit a set of parameters to a model and get a result out 
that matches some experimental data but you have no guarentee
that you have any more that a pretty picture.  For a good example
of what not to do see Gary Harrision differential equation based
modeel of Luckinbill's Paramecium/Didinium experiments in the
Jan 94 Ecology issue in the concepts section.  Real systems are
not deterministic.  If you run a field experiment 20 times you
will get 20 results and hope that there is enough commonality
to get statistical power.  Therefore, the result you are
to which you are callibrating is just a sample from a statistical
distribution.  If that distribution has a wide varience then you
may have fine-tuned your model to an point far from the expected
behavior.  

A second trap is that if your assumption of the basic mechanisim
is incorrect you may fine-tune to a different system that has
the same result for that set of parameters.

Unfortunatly, I don't has a good set of procedures to eleminate 
these hazzards.  I am also not saying that this is a bad method,
it happens to be one I saw abused in an attempt to justify
the use of a differential equation based mode.

Doug Donalson

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* Doug Donalson                          * Office: (805) 893-2962         *
* Ecology, Evolution, and Marine Biology * Home:   (805) 961-4447         *
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* Santa Barbara Ca. 93106                *                                *
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*       Isaac Asimov                                                      *
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On Thu, 17 Apr 1997, Jan Kreft wrote:

> OK, I agree with Paul and Mike that it can be very tricky to determine the
> parameters for individuals. Bacteria as individuals, e. g., are simply so
> small that only the latest high-tech methods could give estimates for the
> parameters you would have to use in a model (and that costs a lot of
> timemoney). Almost always microbiologists measure the population average
> and disregard the heterogeneity of the population. 
> 
> But I can see another way to solve the problem. If you start with a
> conceptual model with all the parameters and mechanics you need and only a
> rough idea of actual values (from population average measurements) you can
> run the sim and compare the output with the real system to be modeled.
> Then you optimize the parameters to achieve the desired output. Perhaps
> call it back-calibration. (Is there an official term for it?) 
> 
> For that purpose, you need a parameter manager (see previous discussion
> with "parameter" in the subject line) to allow a search through param
> space in an evolutionary fashion. As far as I can tell, Gecko's param
> manager is (the only one?) suited for that task. 
> 
> BTW, does IbM hurt also? If so, sorry for that ;-). Point being is that
> that's the term used in the literature and if I want to search for new
> literature, I rely on this keyword. Therefore I would want to use this
> keyword myself sometime. 
> 
> Cheers,
> 
> Jan.
> 
> Mike Brown wrote:
> 
> > 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
> > 
> > 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
> 
> 
> 
> 
> 
>                   ==================================
>    Swarm-Modelling is for discussion of Simulation and Modelling techniques
>    esp. using Swarm.  For list administration needs (esp. [un]subscribing),
>    please send a message to <address@hidden> with "help" in the
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