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How new concepts become universal scientific approaches: insights from citation network analysis of agent-based complex systems science

机译:新概念如何成为通用的科学方法:基于代理的复杂系统科学的引文网络分析的见解

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摘要

Progress in understanding and managing complex systems comprised of decision-making agents, such as cells, organisms, ecosystems or societies, is—like many scientific endeavours—limited by disciplinary boundaries. These boundaries, however, are moving and can actively be made porous or even disappear. To study this process, I advanced an original bibliometric approach based on network analysis to track and understand the development of the model-based science of agent-based complex systems (ACS). I analysed research citations between the two communities devoted to ACS research, namely agent-based (ABM) and individual-based modelling (IBM). Both terms refer to the same approach, yet the former is preferred in engineering and social sciences, while the latter prevails in natural sciences. This situation provided a unique case study for grasping how a new concept evolves distinctly across scientific domains and how to foster convergence into a universal scientific approach. The present analysis based on novel hetero-citation metrics revealed the historical development of ABM and IBM, confirmed their past disjointedness, and detected their progressive merger. The separation between these synonymous disciplines had silently opposed the free flow of knowledge among ACS practitioners and thereby hindered the transfer of methodological advances and the emergence of general systems theories. A surprisingly small number of key publications sparked the ongoing fusion between ABM and IBM research. Beside reviews raising awareness of broad-spectrum issues, generic protocols for model formulation and boundary-transcending inference strategies were critical means of science integration. Accessible broad-spectrum software similarly contributed to this change. From the modelling viewpoint, the discovery of the unification of ABM and IBM demonstrates that a wide variety of systems substantiate the premise of ACS research that microscale behaviours of agents and system-level dynamics are inseparably bound.
机译:像许多科学努力一样,在理解和管理由决策者组成的复杂系统(如细胞,有机体,生态系统或社会)方面的进步,受到学科界限的限制。但是,这些边界正在移动并且可以主动地变得多孔甚至消失。为了研究此过程,我提出了一种基于网络分析的原始文献计量方法,以跟踪和理解基于代理的复杂系统(ACS)的基于模型的科学的发展。我分析了致力于ACS研究的两个社区之间的研究引用,即基于代理的(ABM)和基于个人的建模(IBM)。这两个术语都指的是相同的方法,但是前者在工程和社会科学中是首选,而后者在自然科学中占优势。这种情况提供了一个独特的案例研究,以了解新概念如何在科学领域中显着发展,以及如何促进融合为通用科学方法。基于新颖的异性引用度量的当前分析揭示了ABM和IBM的历史发展,证实了它们过去的脱节性,并发现了它们的逐步合并。这些同义学科之间的分离默默地反对ACS从业者之间知识的自由流动,从而阻碍了方法学进展的转移和通用系统理论的出现。数量惊人的关键出版物激起了ABM和IBM研究之间的持续融合。除了提高人们对广谱问题认识的评论之外,用于模型制定的通用协议和超越边界的推理策略是科学整合的关键手段。可访问的广谱软件同样促成了这一变化。从建模的角度来看,ABM和IBM统一的发现表明,各种各样的系统证实了ACS研究的前提,即代理的微观行为和系统级动力学是密不可分的。

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