Affiliation:
1. Eötvös Loránd University, Budapest, Hungary
2. MTA-ELTE Statistical and Biological Physics Research Group, Budapest, Hungary
Abstract
The living world is full of cohesive collectives that have evolved to move together with high efficiency. Schools of fish or flocks of birds maintain their global direction despite significant noise perturbing the individuals, yet they are capable of performing abrupt collective turns when relevant agitation alters the state of a few members. Ruling local fluctuations out of global movement leads to persistence and requires overdamped interaction dynamics, while propagating swift turns throughout the group leads to responsivity and requires underdamped interaction dynamics. In this paper we show a way to avoid this conflict by introducing a time-dependent leadership hierarchy that adapts locally to
will
: agents’ intention of changing direction. Integrating our new concept of
will
-based inter-agent behaviour highly enhances the responsivity of standard collective motion models, thus enables breaking out of their former limit, the persistence-responsivity trade-off. We also show that the increased responsivity to environmental cues scales well with growing flock size. Our solution relies on active communication or advanced cognition for the perception of
will
. The incorporation of these into collective motion is a plausible hypothesis in higher order species, while it is a realizable feature for artificial robots, as demonstrated by our swarm of 52 drones.
Funder
European Union's Horizon 2020 Research and Innovation Programme
Hungarian National Research, Development and Innovation Office
Subject
Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology
Cited by
26 articles.
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