A common strategy for simplifying complex systems involves partitioning them into subsystems whose behaviors are roughly independent of one another at shorter timescales. Dynamic causal models clarify how doing so reveals a system’s nonequilibrium causal relationships. Here I use these models to elucidate the idealizations and abstractions involved in representing a system at a timescale. The models reveal that key features of causal representations—such as which variables are exogenous—may vary with the timescale at which a system is considered. This has implications for debates regarding which systems can be represented causally.

中文翻译：

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因果表示的近可分解性和时间尺度相关性

简化复杂系统的一种常见策略是将它们划分为子系统，这些子系统的行为在较短的时间范围内大致相互独立。动态因果模型阐明了这样做如何揭示系统的非平衡因果关系。在这里，我使用这些模型来阐明在时间尺度上表示系统所涉及的理想化和抽象化。这些模型揭示了因果表征的关键特征——例如哪些变量是外生的——可能会随着考虑系统的时间尺度而变化。这对关于哪些系统可以因果表示的辩论有影响。