Department of Mathematics, University of British Columbia, Vancouver, British Columbia, V6T 1Z2, Canada.
Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, T6G 2G1, Canada.
PLoS One. 2018 Jun 14;13(6):e0198550. doi: 10.1371/journal.pone.0198550. eCollection 2018.
Direction-dependent interaction rules are incorporated into a one-dimensional discrete-time stochastic individual-based model (IBM) of collective behavior to compare pattern formation with an existing partial differential equation (PDE) model. The IBM is formulated in terms of three social interaction forces: repulsion, alignment, and attraction, and includes information regarding conspecifics' direction of travel. The IBM produces a variety of spatial patterns which qualitatively match patterns observed in a PDE model. The addition of direction-dependent interaction rules exemplifies how directional information transfer within a group of individuals can result in enriched pattern formation. Our individual-based modelling framework reveals the influence that direction-dependent interaction rules such as biological communication can have upon individual movement trajectories and how these trajectories combine to form group patterns.
方向相依交互规则被整合到一个一维离散时间随机个体基础模型(IBM)中,以比较模式形成与现有的偏微分方程(PDE)模型。IBM 是根据三种社会相互作用力来构建的:排斥力、对齐力和吸引力,并包含有关同种个体运动方向的信息。IBM 产生了各种空间模式,这些模式在质量上与 PDE 模型中观察到的模式相匹配。方向相依交互规则的加入说明了在个体群体中传递方向信息如何导致更丰富的模式形成。我们的基于个体的建模框架揭示了方向相依交互规则(如生物通讯)对个体运动轨迹的影响,以及这些轨迹如何组合形成群体模式。