Abstract
Animals making a group sometimes approach and sometimes avoid a dense area of group mates, and that reveals the ambiguity of density preference. Although the ambiguity is not expressed by a simple deterministic local rule, it seems to be implemented by probabilistic inference that is based on Bayesian and inverse Bayesian inference. In particular, the inverse Bayesian process refers to perpetual changing of hypotheses. We here analyse a time series of swarming soldier crabs and show that they are employed to Bayesian and inverse Bayesian inference. Comparing simulation results with data of the real swarm, we show that the interpretation of the movement of soldier crabs which can be based on the inference can lead to the identification of a drastic phase shift-like transition of gathering and dispersing.This article is part of the theme issue ‘Dissipative structures in matter out of equilibrium: from chemistry, photonics and biology (part 2)’.
Highlights
As Ilya Prigogine proposed the notion of dissipative structure [1], biological structures as well as the dynamics of population and collective motion drew an extensive and intense interest for studies inspired by this approach
We have shown how inherent noise can actively contribute to the establishment and maintenance of a robust swarm acting as one unity by comparing a computer model based on an organism’s mutual anticipation with kinetic data from soldier crabs [24,25,26,27,28] and fish schools [29]
Through simulating studies of the model based on Bayesian and inverse Bayesian (BIB) inference, we show that phase transition-like temporal change of polarization found in the swarm of soldier crabs could be explained by switching of approaching or avoiding a swarm resulting from BIB inference
Summary
As Ilya Prigogine proposed the notion of dissipative structure [1], biological structures as well as the dynamics of population and collective motion drew an extensive and intense interest for studies inspired by this approach. We have shown how inherent noise can actively contribute to the establishment and maintenance of a robust swarm acting as one unity by comparing a computer model based on an organism’s mutual anticipation with kinetic data from soldier crabs [24,25,26,27,28] and fish schools [29]. Both in the model and real data, a swarm can be characterized as having high density and a wide variety of polarization. Through simulating studies of the model based on BIB inference, we show that phase transition-like temporal change of polarization found in the swarm of soldier crabs could be explained by switching of approaching or avoiding a swarm resulting from BIB inference
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