yet another spiffy SwarmFest talk!

[Marcus G. Daniels]

An Efficiency Measure for Agent-Based Modeling
Jay Palmer <address@hidden>
NOAA Environmental Technology Laboratory

Agent based modeling is in need of a quantitative optimization
criterion to help remove the arbitrariness in selections of model
parameters.  This talk proposes the use of an efficiency measure that
I call "algorithmic efficiency" for establishing this needed
optimization criterion.  Algorithmic efficiency is defined as the
mutual information between model-predicted patterns and observed
patterns divided by the computational memory used by the model.  This
efficiency has been proven to be bounded between zero and one as
efficiencies ought to be.  Because this efficiency is based on a
statistic (mutual information), the optimizations will be founded on
the statistical disciplines required of complex systems modeling. 
Identifying the computational memory as the fundamental resource is
particularly appropriate for memory intensive agent-based models. 
However, that does not preclude the joint use of other optimization
criteria through the use of utility functions involving the
algorithmic efficiency, Lagrange multipliers, and selected constraints
such as computational speed.


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