Randomness in the choice of neighbours promotes cohesion in mobile animal groups
Vivek Jadhav, Vishwesha Guttal, Danny Raj M

TL;DR
This study demonstrates that in animal groups, randomly choosing a single neighbor for interaction can effectively maintain cohesion, challenging the traditional emphasis on local averaging with multiple neighbors.
Contribution
The paper introduces a spatially-explicit model showing that random neighbor selection alone can sustain group cohesion, supported by a graph-theoretic analysis of interaction networks.
Findings
Random neighbor choice maintains cohesion effectively.
Random interactions create well-connected networks.
Random neighbor selection outperforms nearest neighbor interactions.
Abstract
Classic computational models of collective motion suggest that simple local averaging rules can promote many observed group level patterns. Recent studies, however, suggest that rules simpler than local averaging may be at play in real organisms; for example, fish stochastically align towards only one randomly chosen neighbour and yet the schools are highly polarised. Here, we ask -- how do organisms maintain group cohesion? Using a spatially-explicit model, inspired from empirical investigations, we show that group cohesion can be achieved even when organisms randomly choose only one neighbour to interact with. Cohesion is maintained even in the absence of local averaging that requires interactions with many neighbours. Furthermore, we show that choosing a neighbour randomly is a better way to achieve cohesion than interacting with just its closest neighbour. To understand how cohesion…
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