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Causality and diagrams for system dynamics

机译:系统动力学的因果关系图

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Polarity and causality are important concepts but have not received much attention in the system dynamics literature. The great effort it takes students to properly understand them has motivated this inquiry. In the framework of a conceptual model of interacting with complex systems, several cognitive tasks are proposed. This paper concentrates on one of them that deals with causal links' polarity. An examination of other approaches that deal with causality and use more or less similar diagram languages shows that usually causality is only very broadly defined, and where it is operationally defined, this is done with respect to events rather than behavior. In contrast to these approaches, system dynamics is about behavior rather than events. We then revisit the traditional criticism of causal loop diagrams and show a way out, but add two new criticisms related to the inability of causal loop diagrams to address behavior: in fact it seems that they are closer to the event-related definition of causality. Also, the impossibility to execute them in simulations means that executable concept-models are to be preferred: they express important information a causal loop diagram cannot represent and on top of it they render the behavioral consequences visible (as opposed to the events). In conclusion, causal loop diagrams should only be used by experienced modelers, and be banned from educational use.
机译:极性和因果关系是重要的概念,但在系统动力学文献中并未受到太多关注。学生需要付出巨大的努力才能正确理解他们,这激发了这一探究。在与复杂系统交互的概念模型的框架中,提出了一些认知任务。本文着重讨论其中一个涉及因果关系极性的问题。对其他处理因果关系并使用或多或少相似的图表语言的方法的研究表明,因果关系通常仅在非常宽泛的范围内定义,并且在可操作性定义的地方,这是针对事件而非行为进行的。与这些方法相反,系统动力学是关于行为而不是事件。然后,我们回顾对因果循环图的传统批评,并指出一条出路,但是添加了两个与因果循环图无法解决行为有关的新批评:实际上,它们似乎更接近于事件相关的因果关系定义。同样,不可能在模拟中执行它们意味着可执行概念模型将是首选:它们表达因果循环图无法表示的重要信息,并且最重要的是,它们使行为后果可见(与事件相对)。总之,因果关系图仅应由经验丰富的建模人员使用,并禁止用于教育用途。

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