Autonomous change of behavior for environmental context: An intermittent search model with misunderstanding search pattern

Hisashi Murakami*, Yukio Gunji

*この研究の対応する著者

    研究成果: Conference contribution

    抄録

    Although foraging patterns have long been predicted to optimally adapt to environmental conditions, empirical evidence has been found in recent years. This evidence suggests that the search strategy of animals is open to change so that animals can flexibly respond to their environment. In this study, we began with a simple computational model that possesses the principal features of an intermittent strategy, i.e., careful local searches separated by longer steps, as a mechanism for relocation, where an agent in the model follows a rule to switch between two phases, but it could misunderstand this rule, i.e., the agent follows an ambiguous switching rule. Thanks to this ambiguity, the agent's foraging strategy can continuously change. First, we demonstrate that our model can exhibit an optimal change of strategy from Brownian-type to Lévy-type depending on the prey density, and we investigate the distribution of time intervals for switching between the phases. Moreover, we show that the model can display higher search efficiency than a correlated random walk.

    本文言語English
    ホスト出版物のタイトルInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2016
    出版社American Institute of Physics Inc.
    1863
    ISBN(電子版)9780735415386
    DOI
    出版ステータスPublished - 2017 7 21
    イベントInternational Conference of Numerical Analysis and Applied Mathematics 2016, ICNAAM 2016 - Rhodes, Greece
    継続期間: 2016 9 192016 9 25

    Other

    OtherInternational Conference of Numerical Analysis and Applied Mathematics 2016, ICNAAM 2016
    国/地域Greece
    CityRhodes
    Period16/9/1916/9/25

    ASJC Scopus subject areas

    • 物理学および天文学(全般)

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