19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

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

      Proceedings of the Royal Society B: Biological Sciences
      The Royal Society

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          <p class="first" id="d7398858e132">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. </p>

          Related collections

          Most cited references33

          • Record: found
          • Abstract: not found
          • Article: not found

          Understanding the Complexity of Economic, Ecological, and Social Systems

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Assortative Mixing in Networks

            M. Newman (2002)
            A network is said to show assortative mixing if the nodes in the network that have many connections tend to be connected to other nodes with many connections. Here we measure mixing patterns in a variety of networks and find that social networks are mostly assortatively mixed, but that technological and biological networks tend to be disassortative. We propose a model of an assortatively mixed network, which we study both analytically and numerically. Within this model we find that networks percolate more easily if they are assortative and that they are also more robust to vertex removal.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Strong Inference: Certain systematic methods of scientific thinking may produce much more rapid progress than others.

                Bookmark

                Author and article information

                Journal
                Proceedings of the Royal Society B: Biological Sciences
                Proc. R. Soc. B
                The Royal Society
                0962-8452
                1471-2954
                March 07 2018
                March 14 2018
                March 07 2018
                March 14 2018
                : 285
                : 1874
                : 20172360
                Article
                10.1098/rspb.2017.2360
                5879153
                29514968
                a91a0c1f-b431-4652-ace5-ec7db772ce63
                © 2018
                History

                Comments

                Comment on this article