Examining the role of finite reaction times in swarming models

Modeling collective behavior in biological and artificial systems has had much success in recent years at predicting and mimicing real systems by utilizing techniques borrowed from modelling many particle systems interacting with physical forces. However unlike inert particles interacting with instantaneous forces, living organisms have finite reaction times, and behaviors that vary from individual to individual. What constraints do these physiological effects place on the interactions between individuals in order to sustain a robust ordered state? We use a self-propelled agent based model in continuous space based on previous models by Vicsek and Couzin including alignment and separation maintaining interactions to examine the behavior of a single cohesive group of organisms. We found that for very short reaction times the system is able to form an ordered state even in the presence of heterogeneities. However for larger more physiological reaction times organisms need a buffer zone with no cohesive interactions in order to maintain an ordered state. Finally swarms with finite reaction times and behavioral heterogeneities are able to dynamically sort out individuals with impaired function and sustain order.