论文标题
将重要的循环无缝整合到模型开发和分析中
Seamlessly Integrating Loops That Matter into Model Development and Analysis
论文作者
论文摘要
理解为什么模型以他们的方式行事对于向他们学习的方式至关重要，并将他们提供的见解传达给广泛的受众。重要方法论的循环自动显示了哪些循环在每个时间点占主导地位，并从可调节的一组重要循环中生成简化的因果环图。本文描述了将这些工具与开发的解决方案一起实施到功能齐全的模型开发环境中的挑战。该工具的承诺（如果有的话）被此实施的结果放大了，我们给出了使用工具的几个示例。对于重要的教学模型循环，可以在超速和深度学习的同时简化沟通。对于复杂模型，工具允许以动画简化的因果环图的形式提取对行为的现实解释。对于具有离散元素和不连续元素的模型，仍然很容易发现更大的反馈图片。虽然无疑会对交付的工具进行改进和增强，但它们代表了我们从概念化到交付的模型的能力迈出的一大步。
Understanding why models behave the way they do is critical to learning from them, and to conveying the insights they offer to a broad audience. The Loops that Matter methodology automatically shows which loops are dominating behavior at each point in time and generates simplified causal loop diagrams from a user adjustable set of important loops. This paper describes the challenges of implementing these tools into a fully functioning model development environment along with the solutions developed. The promise of the tools has, if anything, been amplified by the results of this implementation, and we give several examples of using the tools. For pedagogical models Loops that Matter can ease communication while speeding and deepening learning. For complex models the tools allow the extraction of realistic explanations of behavior in the form of animated simplified causal loop diagrams. For models with discrete and discontinuous elements, the bigger feedback picture is still easily discoverable. While there will doubtless be refinements and enhancement to the delivered tools, they represent a large step forward in our ability to understand models from conceptualization through delivery.
