Analysis of Boid Algorithm Weights using Alignment Clustering Index

Abstract

Fish that engage in a school often exhibit unique patterns. Schooling behaviour itself has multiple benefits, among them increasing their likelihood of obtaining food and reducing the risk of predator threats. One of the methods used to simulate this behaviour is boid, proposed by Reynolds. There are three main rules that govern how each boid moves in a group: cohesion, alignment, and separation. Each rule is controlled by a weight parameter that could be changed to encourage or discourage certain rules. This study is aimed at analysing the boid weight parameters, specifically cohesion and alignment, utilizing the Alignment Clustering Index (ACI). The findings indicate that as the weight of alignment increases and the weight of cohesion decreases, boids tend to exhibit more pronounced flocking behaviour. On the contrary, as the weight of cohesion increases and alignment weight decreases, boids move as smaller subgroups comprising about 2-3 members each.