Building Computational Models of Swarms from Simulated Positional Data

A computational method that automatically builds dynamical models of swarming systems from positional data is introduced. As an initial test for the approach, the classical Vicsek model is used to make samples for the computer algorithm and retrieve a model. Time dependent separation measures are introduced in order to characterize the dynamics of a system and then compare the behaviors of the source and retrieved model. Cases of low and high density interactions are considered to verify the generality of the models. The results show the retrieved models are capable of emulating the collective behavior well, especially when the interaction structure resembles the one of the source model.