Suppr超能文献

粗粒化作为一种向下因果关系机制。

Coarse-graining as a downward causation mechanism.

作者信息

Flack Jessica C

机构信息

Santa Fe Institute, Santa Fe, NM 87501, USA

出版信息

Philos Trans A Math Phys Eng Sci. 2017 Dec 28;375(2109). doi: 10.1098/rsta.2016.0338.

Abstract

Downward causation is the controversial idea that 'higher' levels of organization can causally influence behaviour at 'lower' levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks.This article is part of the themed issue 'Reconceptualizing the origins of life'.

摘要

向下因果关系是一个存在争议的观点,即“更高”层次的组织能够对“更低”层次的组织的行为产生因果影响。在此我提出,我们可以通过实际操作并研究适应性系统如何在进化或学习过程中识别规律,并利用这些规律来指导行为,从而深入理解向下因果关系。我认为,在许多适应性系统中,组件通过粗粒化共同计算它们的宏观世界。我进一步提出,当组件根据对共同计算出的宏观属性的估计来调整行为时,我们就从简单反馈转向了向下因果关系。我引入了向下因果关系的弱概念和强概念,并讨论了强形式在新组织层次起源中所起的作用。我用生物和社会系统以及深度神经网络研究中的例子来说明这些观点。本文是主题为“重新认识生命的起源”的特刊的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9c5/5686398/4d93a4452c0c/rsta20160338-g1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验