Axenie Cristian, López-Corona Oliver, Makridis Michail A, Akbarzadeh Meisam, Saveriano Matteo, Stancu Alexandru, West Jeffrey
Department of Computer Science and Center for Artificial Intelligence, Nuremberg Institute of Technology Georg Simon Ohm, Nuremberg, Germany.
Investigadores por México (IxM) at Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), Universidad Nacional Autónoma de México (UNAM), Ciudad Universitaria, CDMX, México.
ArXiv. 2023 Dec 21:arXiv:2312.13991v1.
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 interventional (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.
反脆弱性描述了一个动态系统从环境扰动的变异性中获得的益处。反脆弱性有一个精确的定义,它量化了系统对输入变异性的输出响应。系统可能对扰动反应不佳(脆弱),也可能从扰动中受益(反脆弱)。在本手稿中,我们回顾了反脆弱性理论在技术系统(如交通控制、机器人技术)和自然系统(如癌症治疗、抗生素)中的一系列应用。虽然跨学科用于量化和应用反脆弱性的方法有广泛的重叠,但需要精确界定反脆弱性起作用的尺度。因此,我们简要概述了应用系统中反脆弱性的特性,并回顾了自然系统和技术系统反脆弱性的相关文献。我们将这一综述置于技术系统共有的三个尺度框架内:内在(输入-输出非线性)、遗传(外在环境信号)和干预(反馈控制),在生物系统中有相关对应:生态(同质系统)、进化(异质系统)和干预(控制)。我们使用通用术语来设计在各个尺度上表现出反脆弱行为的系统,并引导读者了解脆弱性-适应性-恢复力-稳健性-反脆弱性的范围、其背后的原理及其实际意义。