Different Facets for Different Experts: A Framework for Streamlining The Integration of Qualitative Insights into ABM Development

Vivek Nallur, Pedram Aghaei, Graham Finlay
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Abstract

A key problem in agent-based simulation is that integrating qualitative insights from multiple discipline experts is extremely hard. In most simulations, agent capabilities and corresponding behaviour needs to be programmed into the agent. We report on the architecture of a tool that disconnects the programmed functions of the agent, from the acquisition of capability and displayed behaviour. This allows multiple different domain experts to represent qualitative insights, without the need for code to be changed. It also allows a continuous integration (or even change) of qualitative behaviour processes, as more insights are gained. The consequent behaviour observed in the model is both, more faithful to the expert's insight as well as able to be contrasted against other models representing other insights.
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不同专家不同面:简化将定性洞察纳入 ABM 开发的框架
基于代理的仿真中的一个关键问题是,整合来自多个学科专家的定性意见极其困难。在大多数模拟中,需要将代理能力和相应行为编程到代理中。我们报告了一种工具的结构,它能将代理的编程功能与获取能力和显示行为分离开来。这样,多个不同领域的专家就可以表达定性的见解,而无需更改代码。它还允许在获得更多见解时,持续整合(甚至改变)定性行为过程。因此,在模型中观察到的行为既更忠实于专家的见解,又能与代表其他见解的其他模型进行对比。
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