Antifragility in complex dynamical systems

Cristian Axenie, Oliver López-Corona, Michail A. Makridis, Meisam Akbarzadeh, Matteo Saveriano, Alexandru Stancu, Jeffrey West
{"title":"Antifragility in complex dynamical systems","authors":"Cristian Axenie, Oliver López-Corona, Michail A. Makridis, Meisam Akbarzadeh, Matteo Saveriano, Alexandru Stancu, Jeffrey West","doi":"10.1038/s44260-024-00014-y","DOIUrl":null,"url":null,"abstract":"Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations. Antifragility carries a precise definition that quantifies a system’s output response to input variability. Systems may respond poorly to perturbations (fragile) or benefit from perturbations (antifragile). In this manuscript, we review a range of applications of antifragility theory in technical systems (e.g., traffic control, robotics) and natural systems (e.g., cancer therapy, antibiotics). While there is a broad overlap in methods used to quantify and apply antifragility across disciplines, there is a need for precisely defining the scales at which antifragility operates. Thus, we provide a brief general introduction to the properties of antifragility in applied systems and review relevant literature for both natural and technical systems’ antifragility. We frame this review within three scales common to technical systems: intrinsic (input–output nonlinearity), inherited (extrinsic environmental signals), and induced (feedback control), with associated counterparts in biological systems: ecological (homogeneous systems), evolutionary (heterogeneous systems), and interventional (control). We use the common noun in designing systems that exhibit antifragile behavior across scales and guide the reader along the spectrum of fragility–adaptiveness–resilience–robustness–antifragility, the principles behind it, and its practical implications.","PeriodicalId":501707,"journal":{"name":"npj Complexity","volume":" ","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44260-024-00014-y.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Complexity","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s44260-024-00014-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations. Antifragility carries a precise definition that quantifies a system’s output response to input variability. Systems may respond poorly to perturbations (fragile) or benefit from perturbations (antifragile). In this manuscript, we review a range of applications of antifragility theory in technical systems (e.g., traffic control, robotics) and natural systems (e.g., cancer therapy, antibiotics). While there is a broad overlap in methods used to quantify and apply antifragility across disciplines, there is a need for precisely defining the scales at which antifragility operates. Thus, we provide a brief general introduction to the properties of antifragility in applied systems and review relevant literature for both natural and technical systems’ antifragility. We frame this review within three scales common to technical systems: intrinsic (input–output nonlinearity), inherited (extrinsic environmental signals), and induced (feedback control), with associated counterparts in biological systems: ecological (homogeneous systems), evolutionary (heterogeneous systems), and interventional (control). We use the common noun in designing systems that exhibit antifragile behavior across scales and guide the reader along the spectrum of fragility–adaptiveness–resilience–robustness–antifragility, the principles behind it, and its practical implications.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
复杂动力系统中的反脆弱
反脆弱度描述了动态系统从环境扰动变化中获得的益处。反脆弱有一个精确的定义,可以量化系统对输入变化的输出响应。系统对扰动的反应可能很差(脆弱),也可能从扰动中受益(反脆弱)。在本手稿中,我们回顾了反脆弱理论在技术系统(如交通控制、机器人)和自然系统(如癌症治疗、抗生素)中的一系列应用。虽然各学科量化和应用反脆弱性的方法存在广泛的重叠,但仍有必要精确定义反脆弱性发挥作用的尺度。因此,我们简要介绍了应用系统中反脆弱性的特性,并回顾了自然和技术系统反脆弱性的相关文献。我们在技术系统常见的三个尺度范围内进行回顾:内在(输入-输出非线性)、继承(外在环境信号)和诱导(反馈控制),以及生物系统中的相关对应尺度:生态(同质系统)、进化(异质系统)和干预(控制)。我们在设计跨尺度表现出反脆弱行为的系统时使用了常用名词,并引导读者沿着脆弱性--适应性--复原性--稳健性--反脆弱的光谱,了解其背后的原理及其实际意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Rebound in epidemic control: how misaligned vaccination timing amplifies infection peaks Triangulation for causal loop diagrams: constructing biopsychosocial models using group model building, literature review, and causal discovery How U.S. Presidential elections strengthen global hate networks Author Correction: Networks and identity drive the spatial diffusion of linguistic innovation in urban and rural areas Urban residential clustering and mobility of ethnic groups: impact of fertility
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1