Flocking Behaviour: Agent-Based Simulation and Hierarchical Leadership

Abstract

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Determining shoal membership using affinity propagation

“…Usually, coordinated motion can be seen on the computer screen after several hundreds of time steps. The rules are similar but not identical to those in Huth & Wissel's shoaling and schooling model [29]; for details about MovAgent, see [20,9]. Like Huth & Wissel's model, the graphical display of the simulated motion is perceived to be similar to that of real fish.…”

“…In addition, the data used to test both STAP and human observers should be obtained from dynamics of real shoals. Although the data obtained using our MovAgent simulation program is useful for testing shoal detection methods (see [9,20]), empirical validity based on real shoal data should also be of concern.…”

A Novel Agent-Based Simulation Framework for Sensing in Complex Adaptive Environments

“…Furthermore, as Quera et al [33] have noted, there is no simple index applicable to flocking in agent-based modeling that includes the range of factors describing the degree of flocking behavior. The authors also mention that flockdetection is normally carried out merely by observing the changes in the agents' locations over time on the computer screen.…”

Swarm behavior control of mobile multi-robots with wireless sensor networks

“…Agents can be used to model the behaviors of swarm individuals by rewarding or penalizing their attempted approaches and movements and it has proved to be a new powerful way to study the emergency of swarm behavior (Quera et al, 2010).…”