Emergence of an optimal search strategy from a simple random walk

Tomoko Sakiyama*, Yukio Pegio Gunji


研究成果: Article査読

13 被引用数 (Scopus)


In reports addressing animal foraging strategies, it has been stated that Lévy-like algorithms represent an optimal search strategy in an unknown environment, because of their super-diffusion properties and power-law-distributed step lengths. Here, starting with a simple random walk algorithm, which offers the agent a randomly determined direction at each time step with a fixed move length, we investigated how flexible exploration is achieved if an agent alters its randomly determined next step forward and the rule that controls its random movement based on its own directional moving experiences. We showed that our algorithm led to an effective food-searching performance compared with a simple random walk algorithm and exhibited super-diffusion properties, despite the uniformstep lengths. Moreover, our algorithmexhibited a power-law distribution independent of uniform step lengths.

ジャーナルJournal of the Royal Society Interface
出版ステータスPublished - 2013 9月 6

ASJC Scopus subject areas

  • バイオテクノロジー
  • 生物理学
  • バイオエンジニアリング
  • 生体材料
  • 生化学
  • 生体医工学


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