  Mathematical models for systems of interacting agents using simple local
rules have been proposed and shown to exhibit emergent swarming behavior. Most
of these models are constructed by intuition or manual observations of real
phenomena, and later tuned or verified to simulate desired dynamics. In
contrast to this approach, we propose using a model that attempts to follow an
averaged rule of the essential distance-dependent collective behavior of real
pigeon flocks, which was abstracted from experimental data. By using a simple
model to follow the behavioral tendencies of real data, we show that our model
can exhibit emergent self-organizing dynamics such as flocking, pattern
formation, and counter-rotating vortices. The range of behaviors observed in
our simulations are richer than the standard models of collective dynamics, and
should thereby give potential for new models of complex behavior.
