Social Behavior in a Team of Autonomous Sensors

Abstract

Probabilities of physical attack are often determined by various environmental factors. As the environment changes, the probability of attack associated with an area changes. In such dynamic environments, autonomous sensors are potentially useful to optimally cover regions that have high probabilities of attack. We present results from agent-based simulations, in which autonomous sensors forage a space to find areas with high attack probabilities. Simple heuristics often resulted in optimal coverage of the attack regions, without a centralized control. By varying how quickly sensors respond to a threat, we can encourage some sensors to cover some areas, and others to hang back and defend different areas, allowing them to distribute optimally as a team. The idea of making team members hang back may seem counterintuitive. In fact, people often converge all at once to respond to an immediate threat. Our results show that it is useful to have some agents remain behind, in case the environment changes.