Computational and Structural Biotechnology Journal (Jan 2021)

Lévy Walk in Swarm Models Based on Bayesian and Inverse Bayesian Inference

  • Yukio-Pegio Gunji,
  • Takeshi Kawai,
  • Hisashi Murakami,
  • Takenori Tomaru,
  • Mai Minoura,
  • Shuji Shinohara

Journal volume & issue
Vol. 19
pp. 247 – 260

Abstract

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While swarming behavior is regarded as a critical phenomenon in phase transition and frequently shows the properties of a critical state such as Lévy walk, a general mechanism to explain the critical property in swarming behavior has not yet been found. Here, we address this problem with a simple swarm model, the Self-Propelled Particle (SPP) model, and propose a way to explain this critical behavior by introducing agents making decisions via the data-hypothesis interaction in Bayesian inference, namely, Bayesian and inverse Bayesian inference (BIB). We compare three SPP models, namely, the simple SPP, the SPP with Bayesian-only inference (BO) and the SPP with BIB models. We show that only the BIB model entails coexisting tornado, splash and translation behaviors, and the Lévy walk pattern.

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