Taking the context of simulating a retail environment using agent based modelling, a theoretical model is presented that describes the probability distribution of customer "collisions" using a novel space transformation to the Torus $Tor^2$. A method for generating the distribution of customer paths based on historical basket data is developed. Finally a calculation of the number of simulations required for statistical significance is developed. An implementation of this modelling approach to run simulations on multiple store geometries at industrial scale is being developed with current progress detailed in the technical appendix.

中文翻译：

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模拟超市中的人际互动以大规模衡量 COVID-19 传染的风险

以使用基于代理的建模模拟零售环境为背景，提出了一个理论模型，该模型使用到 Torus $Tor^2$ 的新颖空间变换来描述客户“碰撞”的概率分布。开发了一种基于历史购物篮数据生成客户路径分布的方法。最后，计算出统计显着性所需的模拟次数。正在开发这种建模方法的实现，以在工业规模的多个商店几何图形上运行模拟，当前的进展在技术附录中详细说明。