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超越局部:信息分解方法对因果涌现的综述。

Greater than the parts: a review of the information decomposition approach to causal emergence.

机构信息

Department of Psychology, University of Cambridge, Cambridge, UK.

Department of Psychology, Queen Mary University of London, London, UK.

出版信息

Philos Trans A Math Phys Eng Sci. 2022 Jul 11;380(2227):20210246. doi: 10.1098/rsta.2021.0246. Epub 2022 May 23.

Abstract

Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept, the study of emergence has suffered from a lack of formalisms that could be used to guide discussions and advance theories. Here, we summarize, elaborate on, and extend a recent formal theory of causal emergence based on information decomposition, which is quantifiable and amenable to empirical testing. This theory relates emergence with information about a system's temporal evolution that cannot be obtained from the parts of the system separately. This article provides an accessible but rigorous introduction to the framework, discussing the merits of the approach in various scenarios of interest. We also discuss several interpretation issues and potential misunderstandings, while highlighting the distinctive benefits of this formalism. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

摘要

涌现是一个深奥的主题,跨越了许多科学学科,包括星系的形成以及意识如何从神经元的集体活动中产生。尽管人们对这个概念非常感兴趣,但涌现的研究一直受到缺乏形式主义的限制,这些形式主义本可以用来指导讨论和推进理论。在这里,我们总结、详细阐述并扩展了一种基于信息分解的因果涌现的新形式理论,这种理论是可量化的,并且可以进行经验测试。该理论将涌现与关于系统时间演化的信息联系起来,而这些信息无法从系统的各个部分单独获得。本文为该框架提供了一个易于理解但严格的介绍,讨论了该方法在各种感兴趣的场景中的优点。我们还讨论了几个解释问题和潜在的误解,同时强调了这种形式主义的独特优势。本文是主题为“复杂物理和社会技术系统中的涌现现象:从细胞到社会”的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb77/9125226/1694c4b7d697/rsta20210246f01.jpg

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