[FRIAM] A billion agents

[Douglas Roberts]

Another way to answer this is, "No, it will not be self fulfilling if there
is an appropriate experimental design for using stochastically-generated
input parameters for agents in an ABM system."  EpiSims uses stochastically
generated disease parameters to characterize both the disease agents and the
individual person responses to disease. When the EpiSims runs are made there
are additional stochastic processes that influence population mixing
patterns, with the results being statistically valid, and
non-self-fulfiling.

--Doug
-- 
Doug Roberts, RTI International
droberts at rti.org
doug at parrot-farm.net
505-455-7333 - Office
505-670-8195 - Cell

On 10/9/06, Marcus G. Daniels <mgd at santafe.edu> wrote:
>
> Raymond Parks wrote:
> > Russell Standish suggested that one could specify large quantities of
> > similiar but not exactly the same agents:
> >
> >
> >> By setting their behaviour parameters from a probability distribution.
> >>
> >
> >    But isn't this self-fulfilling?  If you collect data about behaviours
> > to populate your probability distribution you will be programming your
> > agents to act the way you collected your data.  If, by chance or design,
> > your data collection is biased, your agents will be biased.
> >
> Being distributions, the parameters (the mixing ratios of different
> kinds of agent behaviors) will have random peturbations around typical
> values and in a large or long enough run you'll witness the consequences
> of how this bias might play out at a global level.
>
> The bigger the computers, the wider variances of agent mixes that can be
> measured.
>
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