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Quantitative measures of crowd patterns in agent-based models of street protests

机译:基于主体的街头抗议模型中人群模式的量化度量

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In this work we describe the introduction of quantitative measures of emergent crowd patterns in an existing Agent-Based model (ABM) of street protests with multiple actors (police, protester and `media' agents). The model was applied to a scenario of a police force defending a government building which protesters seek to invade. The improved model provided a coherent `narrative' of the simulations and highlighted the realistic and unrealistic aspects of the agents' interactions. Two new types of police agents - `defensive' and `offensive' - were introduced, leading to a realistic model representation of police cordons defending a site or charging to disperse clusters of violent protesters. The new quantitative measures provided information on cluster size and orientation of clusters of violent protesters, as well as police coverage and protester breaching of the defensive perimeter, together with the time history of the bursts of localized fights and arrests. It was shown how the quantitative measures of the emergent properties can be used for both parameterization and validation of the model.
机译:在这项工作中,我们描述了在具有多个参与者(警察,抗议者和“媒体”代理)的街头抗议活动的现有基于代理的模型(ABM)中引入紧急人群模式的定量测量方法。该模型适用于警察保卫抗议者试图入侵的政府大楼的场景。改进的模型提供了模拟的连贯“叙述”,并突出了代理交互的现实和不现实方面。引入了两种新型的警务人员-“防御型”和“进攻型”,从而形成了警戒线捍卫现场或指控驱散暴力示威者的现实模型代表。新的量化措施提供了有关暴力抗议者群体规模和取向的信息,以及警察的覆盖范围和抗议者违反防御范围的信息,以及局部战斗和逮捕事件爆发的时间历史。它显示了如何将涌现特性的定量度量用于模型的参数化和验证。

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