Inverse Bayesian inference in swarming behaviour of soldier crabs

Yukio Gunji, Hisashi Murakami, Takenori Tomaru, Vasileios Basios

    Research output: Contribution to journalArticle

    6 Citations (Scopus)

    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)’.

    Original languageEnglish
    Article number20170370
    JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
    Volume376
    Issue number2135
    DOIs
    Publication statusPublished - 2018 Dec 28

    Keywords

    • Bayesian inference
    • Collective behaviour
    • Polarization
    • Soldier crabs
    • Swarm

    ASJC Scopus subject areas

    • Mathematics(all)
    • Engineering(all)
    • Physics and Astronomy(all)

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