Emergence of a coherent and cohesive swarm based on mutual anticipation

Abstract

Collective behavior emerging out of self-organization is one of the most striking properties of an animal group. Typically, it is hypothesized that each individual in an animal group tends to align its direction of motion with those of its neighbors. Most previous models for collective behavior assume an explicit alignment rule, by which an agent matches its velocity with that of neighbors in a certain neighborhood, to reproduce a collective order pattern by simple interactions. Recent empirical studies, however, suggest that there is no evidence for explicit matching of velocity, and that collective polarization arises from interactions other than those that follow the explicit alignment rule. We here propose a new lattice-based computational model that does not incorporate the explicit alignment rule but is based instead on mutual anticipation and asynchronous updating. Moreover, we show that this model can realize densely collective motion with high polarity. Furthermore, we focus on the behavior of a pair of individuals, and find that the turning response is drastically changed depending on the distance between two individuals rather than the relative heading, and is consistent with the empirical observations. Therefore, the present results suggest that our approach provides an alternative model for collective behavior.

Mutual anticipation can contribute to self-organization in human crowds

“…Furthermore, future studies focusing on anticipation in human crowds might bring innovative perspectives in other research fields concerned with self-organizing systems in general. For example, anticipatory behavior contributes to cooperative human decision-making through synchronization between two persons (13,15); animal groups are considered to achieve robust collective behavior through mutual anticipation (25)(26)(27)(28)(29)(30); and swarm robotics has problems in navigation and collision avoidance in the real world and needs a previously unknown approach in industrial applications (31). Anticipation likely plays a key role in a wide range of self-organizing systems.…”

Mutual anticipation can contribute to self-organization in human crowds

“…Moreover, future studies focusing on anticipation in human crowds might open new perspectives in other research fields concerned with self-organizing systems in general. For example, anticipatory behavior contributes to cooperative human decision-making through synchronization between two persons [15,18]; animal groups are considered to achieve robust collective behavior through mutual anticipation [46][47][48][49][50]; and swarm robotics has problems in navigation and collision avoidance in the real world and needs a new approach in industrial applications [51]. Anticipation likely plays a key role in a wide range of self-organizing systems.…”

Assembly along lines in boundary-driven dynamical system

“…While the non-local rule appears to be unphysical for most natural systems in which interactions are local in character, it can be implemented in artificial agent systems e.g., robots that can communicate across arbitrary distances. In recent years, self-organization and collective behavior in swarms of robots where a large number of robots interact using an simple algorithm has gained lot of attention [18][19][20][21][22][23][24] .…”