Abstract
Abstract
The study of self-propelled particles is a fast growing research topic where biological inspired movement is increasingly becoming of much interest. A relevant example is the collective motion of social insects, whose variety and complexity offer fertile grounds for theoretical abstractions. It has been demonstrated that the collective motion involved in the searching behaviour of termites is consistent with self-similarity, anomalous diffusion and Lévy walks. In this work we use visibility graphs—a method that maps time series into graphs and quantifies the signal complexity via graph topological metrics—in the context of social insects foraging trajectories extracted from experiments. Our analysis indicates that the patterns observed for isolated termites change qualitatively when the termite density is increased, and such change cannot be explained by jamming effects only, pointing to collective effects emerging due to non-trivial foraging interactions between insects as the cause. Moreover, we find that such onset of complexity is maximised for intermediate termite densities.
Funder
Agencia Estatal de Investigación
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Universidad Nacional Autónoma de México
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems
Cited by
1 articles.
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