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.
Original language | English |
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Article number | 2667 |
Journal | Applied Sciences (Switzerland) |
Volume | 9 |
Issue number | 13 |
DOIs | |
Publication status | Published - 1 Jul 2019 |
Externally published | Yes |
Keywords
- Agent-based collective intelligence
- Biologically inspired approaches and methods
- Collective foraging
- Methodologies for agent-based systems
- Multi-agent complex systems
- Multi-robot simulation
- Physics-based simulation
- Power law distribution
- Scale-free properties