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.
Scale-free features in collective robot foraging
2019-01-01
APPLIED SCIENCES-BASEL ; ISSN: 2076-3417
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Technology and Engineering , DECISION-MAKING , SWARM , SYSTEMS , DISTRIBUTIONS , PRINCIPLES , ALGORITHM , PATTERNS , FLOCKING , MODEL , 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
DDC: | 629 |
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