Collective decision making in cohesive flocks

TL;DR

This paper presents a simple model combining self-propelled particles and a random field Ising model to understand how cohesive flocks, like birds, make collective landing decisions, capturing sharp transitions in behavior.

Contribution

It introduces a novel modeling approach that integrates boundary conditions and decision propagation rules to simulate collective decision making in flocking animals.

Findings

The model reproduces sharp collective switching from flying to landing.

It captures the influence of individual intention variance and external pressure.

The transition in collective behavior is much sharper than individual intentions distribution.

Abstract

Most of us must have been fascinated by the eye catching displays of collectively moving animals. Schools of fish can move in a rather orderly fashion and then change direction amazingly abruptly. There are a huge number of further examples both from the living and the non-living world for phenomena during which the many interacting, permanently moving units seem to arrive at a common behavioural pattern taking place in a short time. As a paradigm of this type of phenomena we consider the problem of how birds arrive at a decision resulting in their synchronized landing. We introduce a simple model to interpret this process. Collective motion prior to landing is modelled using a simple self-propelled particle (SPP) system with a new kind of boundary condition, while the tendency and the sudden propagation of the intention of landing is introduced through rules analogous to the random field Ising model in an external field. We show that our approach is capable of capturing the most relevant features of collective decision making in a system of units with a variance of individual intentions and being under an increasing level of pressure to switch states. We find that as a function of the few parameters of our model the collective switching from the flying to the landing state is indeed much sharper than the distribution of the individual landing intentions. The transition is accompanied by a number of interesting features discussed in this report.