fest discussion

[Doug Donalson;]

Is anyone interested in putting together and discussion
group on model testing and verification at SWARM fest?

Here is my "take" on it with examples from my research.

One of the most difficult and important aspects of complex
modeling is that of model testing and verification.  It 
falls into two broad catagories, verifying that the model
is bug free, and determining the effects of what I call
model infrastructure.

Two examples of the first catagory:

Test individual components:

   Ex: I have an agent that in the absence of all other
       effects dies off exponentally so I turn off all
       other effects and confirm that all the individuals 
       die off and that the half life time matches the 
       death rate.

Compare with simpler models:

   Ex: I have a "base line" delay differential equation
       model that provides stability boundries and 
       equlibrium values for a set of parameters.  I
       developed a second model that is the analog of
       the DDE but with the quantization effects associated
       with requiring the number of individuals to be
       an integer.  This is the Stochastic Birth/Death
       or SBD formulation.

       If I force my complex model to be "well mixed" 
       spatially, then it should match the results of the SBD
       for the same system size and parameter choices.  The
       SBD model can then provide the parameter space
       where the quantization stochasticity has a small
       effect on the system dynamics.  This allows a 
       set of parameters or "parameter space" in which 
       my complex model should have very similar results 
       to the DDE model.

       Bottom line: I find a parameter space that if my complex
       model is working correctly it should provide results
       that match those of an analyticaly (or at least
       numerically) tractable model.

The second catagory has to do with the effects that the
actual model implimentation may have on the results.  
This is basically worrying about artifacts from model 
structure.

      Ex: Any time you design a model around a lattice
          structure you by definition quantize space.
          Does this "minium size" of one square have
          a significant effect on the results?

      Ex: When using a synchronous schedule how does the
          ordering of events within a time step affect
          the outcome.  For example, if it was a predator/prey
          simulation, if predation always came before prey
          birth you would potentially expect a different
          outcome then if births came before predation.


I know this is long winded, but these are key issues if
we are to believe and understand the results of complex 
models.  Is anyone interested in tossing around problems
and solutions in these areas?  Let me know if anyone is
interested.

Cheers,

   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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*                                                                         *
*   The most exciting phrase to hear in science, the one that             *
*   heralds new discoveries, is not "EUREKA" (I have found it) but        *
*   "That's funny ...?"                                                   *
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*       Isaac Asimov                                                      *
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