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

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)247-260
Number of pages14
JournalComputational and Structural Biotechnology Journal
Volume19
DOIs
Publication statusPublished - 2021 Jan

Keywords

  • Bayesian inference
  • Critical phenomena
  • Lévy walk
  • Swarm Behavior

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications

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