Rebout Nancy, Lone Jean-Christophe, De Marco Arianna, Cozzolino Roberto, Lemasson Alban, Thierry Bernard
Physiologie de la Reproduction et des Comportements, CNRS, INRAE, Université de Tours, Nouzilly, France.
Fondazione Ethoikos, Radicondoli, Italy.
R Soc Open Sci. 2021 Mar 17;8(3):200895. doi: 10.1098/rsos.200895.
While there is no consensus about the definition of complexity, it is widely accepted that the ability to produce uncertainty is the most prominent characteristic of complex systems. We introduce new metrics that purport to quantify the complexity of living organisms and social organizations based on their levels of uncertainty. We consider three major dimensions regarding complexity: diversity based on the number of system elements and the number of categories of these elements; flexibility which bears upon variations in the elements; and combinability which refers to the patterns of connection between elements. These three dimensions are quantified using Shannon's uncertainty formula, and they can be integrated to provide a tripartite complexity index. We provide a calculation example that illustrates the use of these indices for comparing the complexity of different social systems. These indices distinguish themselves by a theoretical basis grounded on the amount of uncertainty, and the requirement that several aspects of the systems be accounted for to compare their degree of complexity. We expect that these new complexity indices will encourage research programmes aiming to compare the complexity levels of systems belonging to different realms.
虽然对于复杂性的定义尚无共识,但人们普遍认为,产生不确定性的能力是复杂系统最显著的特征。我们引入了新的指标,旨在根据生物体和社会组织的不确定性水平来量化其复杂性。我们考虑了复杂性的三个主要维度:基于系统元素数量及其元素类别数量的多样性;涉及元素变化的灵活性;以及指元素之间连接模式的可组合性。这三个维度使用香农不确定性公式进行量化,并且可以整合以提供一个三方复杂性指数。我们提供了一个计算示例,说明了这些指数在比较不同社会系统复杂性方面的用途。这些指数的独特之处在于其基于不确定性量的理论基础,以及为比较系统的复杂程度而需要考虑系统的多个方面这一要求。我们期望这些新的复杂性指数将鼓励旨在比较不同领域系统复杂性水平的研究项目。