Scale-Free Features in Collective Robot Foraging

Abstract

In many complex systems observed in nature, properties such as scalability, adaptivity, or rapid information exchange are often accompanied by the presence of features that are scale-free, i.e., that have no characteristic scale. Following this observation, we investigate the existence of scale-free features in artificial collective systems using simulated robot swarms. We implement a large-scale swarm performing the complex task of collective foraging, and demonstrate that several space and time features of the simulated swarm—such as number of communication links or time spent in resting state—spontaneously approach the scale-free property with moderate to strong statistical plausibility. Furthermore, we report strong correlations between the latter observation and swarm performance in terms of the number of retrieved items.

Keywords

• agent-based collective intelligence
• multi-agent complex systems
• scale-free properties
• power law distribution
• biologically inspired approaches and methods
• collective foraging
• physics-based simulation
• methodologies for agent-based systems
• multi-robot simulation