Numerical study on the emergence of anisotropy in artificial flocks: A BOIDS modeling and simulations of empirical findings

Abstract

In real flocks, it was revealed that the angular density of nearest neighbors shows a strong {\it anisotropic structure} of individuals by very recent extensive field studies by Ballerini et al [{\it Proceedings of the National Academy of Sciences USA} {\bf 105}, pp.1232-1237 (2008)]. In this paper, we show that this empirical evidence in real flocks, namely, the structure of anisotropy also emerges in an artificial flock simulation based on the {\it BOIDS} by Reynolds [{\it Computer Graphics} {\bf 21}, pp.25-34 (1987)]. We numerically find that appropriate combinations of the weights for just only three essential factors of the BOIDS, namely, `Cohesion', `Alignment' and `Separation' lead to a strong anisotropy in the flock. This result seems to be highly counter-intuitive and also provides a justification of the hypothesis that the anisotropy emerges as a result of self-organization of interacting intelligent agents (birds for instance). To quantify the anisotropy, we evaluate a useful statistics (a kind of {\it order parameters} in statistical physics), that is to say, the so-called $\gamma$-value defined as an inner product between the vector in the direction of the lowest angular density of flocks and the vector in the direction of the moving of the flock. Our results concerning the emergence of the anisotropy through the $\gamma$-value might enable us to judge whether an arbitrary flock simulation seems to be {\it realistic} or not.