| Autor: |
Farkas IJ; Department of Automation Control, Huazhong University of Science and Technology, 1037 Luoyu Rd, Wuhan, China, 430074.; MTA-ELTE Statistical and Biological Physics Research Group, Hungarian Academy of Sciences, Pázmány Péter sétány 1A, Budapest, Hungary, 1117., Wang S; School of Computer Science, Fudan University, 825 Zhangheng Rd, Shanghai, China, 201203. |
| Jazyk: |
angličtina |
| Zdroj: |
PloS one [PLoS One] 2018 May 04; Vol. 13 (5), pp. e0191745. Date of Electronic Publication: 2018 May 04 (Print Publication: 2018). |
| DOI: |
10.1371/journal.pone.0191745 |
| Abstrakt: |
Fish, birds, insects and robots frequently swim or fly in groups. During their three dimensional collective motion, these agents do not stop, they avoid collisions by strong short-range repulsion, and achieve group cohesion by weak long-range attraction. In a minimal model that is isotropic, and continuous in both space and time, we demonstrate that (i) adjusting speed to a preferred value, combined with (ii) radial repulsion and an (iii) effective long-range attraction are sufficient for the stable ordering of autonomously moving agents in space. Our results imply that beyond these three rules ordering in space requires no further rules, for example, explicit velocity alignment, anisotropy of the interactions or the frequent reversal of the direction of motion, friction, elastic interactions, sticky surfaces, a viscous medium, or vertical separation that prefers interactions within horizontal layers. Noise and delays are inherent to the communication and decisions of all moving agents. Thus, next we investigate their effects on ordering in the model. First, we find that the amount of noise necessary for preventing the ordering of agents is not sufficient for destroying order. In other words, for realistic noise amplitudes the transition between order and disorder is rapid. Second, we demonstrate that ordering is more sensitive to displacements caused by delayed interactions than to uncorrelated noise (random errors). Third, we find that with changing interaction delays the ordered state disappears at roughly the same rate, whereas it emerges with different rates. In summary, we find that the model discussed here is simple enough to allow a fair understanding of the modeled phenomena, yet sufficiently detailed for the description and management of large flocks with noisy and delayed interactions. Our code is available at http://github.com/fij/floc. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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