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

研究成果: Article査読

3 被引用数 (Scopus)


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.

ジャーナルComputational and Structural Biotechnology Journal
出版ステータスPublished - 2021 1月

ASJC Scopus subject areas

  • バイオテクノロジー
  • 生物理学
  • 構造生物学
  • 生化学
  • 遺伝学
  • コンピュータ サイエンスの応用


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