论文标题
核对出现：一种信息理论方法，用于识别多元数据中的因果关系
Reconciling emergences: An information-theoretic approach to identify causal emergence in multivariate data
论文作者
论文摘要
广泛的出现概念在各种最具挑战性的开放科学问题中具有重要作用，但是，已经提出了构成新现象的定量理论。本文介绍了多元系统中因果出现的形式理论，该理论研究了系统部分动力学与感兴趣的宏观特征之间的关系。我们的理论提供了对下降因果关系的定量定义，并引入了紧急行为的互补方式 - 我们称这是因果分离。此外，该理论允许在大型系统中有效计算的实际标准，使我们的框架适用于一系列实际关注的情况。我们在许多案例研究中说明了我们的发现，包括康威的生活游戏，雷诺的羊群模型和通过电皮质学测量的神经活动。
The broad concept of emergence is instrumental in various of the most challenging open scientific questions -- yet, few quantitative theories of what constitutes emergent phenomena have been proposed. This article introduces a formal theory of causal emergence in multivariate systems, which studies the relationship between the dynamics of parts of a system and macroscopic features of interest. Our theory provides a quantitative definition of downward causation, and introduces a complementary modality of emergent behaviour -- which we refer to as causal decoupling. Moreover, the theory allows practical criteria that can be efficiently calculated in large systems, making our framework applicable in a range of scenarios of practical interest. We illustrate our findings in a number of case studies, including Conway's Game of Life, Reynolds' flocking model, and neural activity as measured by electrocorticography.
