Determining interaction rules in animal swarms

TL;DR

This paper presents a method to infer local interaction rules in animal swarms by optimizing hypothetical interaction parameters to match observed trajectories, demonstrated through computer simulations.

Contribution

It introduces a novel approach to determine mechanistic interaction rules in animal swarms from trajectory data.

Findings

Successfully reconstructed interaction rules from simulated data

Method minimizes deviation between observed and modeled forces

Applicable to real animal swarm data in future work

Abstract

In this paper we introduce a method for determining local interaction rules in animal swarms. The method is based on the assumption that the behavior of individuals in a swarm can be treated as a set of mechanistic rules. The principal idea behind the technique is to vary parameters that define a set of hypothetical interactions to minimize the deviation between the forces estimated from observed animal trajectories and the forces resulting from the assumed rule set. We demonstrate the method by reconstructing the interaction rules from the trajectories produced by a computer simulation.