Mining of Behavioral Motifs from Individual Ant Trajectory

Abstract

Complex biological systems resemble a “black box,” as it is a priori unclear how interactions among individuals will affect the collective (group) behavioral performance. Network analysis is a suitable method to shed light on these black boxes by studying the collective behavior of highly integrated social organisms such as ants. Individual within the colony have their own personality and task allocation for sustaining the society. Individual-level data are also important for understanding network structure. To obtain individual-level data such as personality and task allocation, individual behavior was assessed using several well-established information processing methods. To detect individual personalities from the position data, trajectory patterns were used. To analyze trajectory patterns, behavioral motif detection was used. The behavioral motif is the minimum unit of the entire trajectory.