We propose a model for memory-based movement of an individual. The dynamics are modeled by a stochastic differential equation, coupled with an eikonal equation, whose potential depends on the individual’s memory and perception. Under a simple periodic environment, we discover that both long and short-term memory with appropriate time scales are essential for producing expected periodic migrations.

中文翻译：

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内存驱动的运动模型，用于定期迁移。

我们提出了一个基于记忆的个人运动模型。动力学是由随机微分方程和一个eikonal方程建模的，该方程的潜力取决于个人的记忆力和感知力。在简单的周期性环境下，我们发现具有适当时间尺度的长期和短期记忆对于产生预期的周期性迁移至关重要。