Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
18
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Beyond collective intelligence: Collective adaptation

      review-article

      Read this article at

      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

          We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for ‘intelligent’ collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

          Related collections

          Most cited references298

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Double-slit photoelectron interference in strong-field ionization of the neon dimer

          Wave-particle duality is an inherent peculiarity of the quantum world. The double-slit experiment has been frequently used for understanding different aspects of this fundamental concept. The occurrence of interference rests on the lack of which-way information and on the absence of decoherence mechanisms, which could scramble the wave fronts. Here, we report on the observation of two-center interference in the molecular-frame photoelectron momentum distribution upon ionization of the neon dimer by a strong laser field. Postselection of ions, which are measured in coincidence with electrons, allows choosing the symmetry of the residual ion, leading to observation of both, gerade and ungerade, types of interference.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Collective dynamics of 'small-world' networks.

            Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Bagging predictors

                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Journal
                J R Soc Interface
                J R Soc Interface
                RSIF
                royinterface
                Journal of the Royal Society Interface
                The Royal Society
                1742-5689
                1742-5662
                March 22, 2023
                March 2023
                March 22, 2023
                : 20
                : 200
                : 20220736
                Affiliations
                [ 1 ] Santa Fe Institute, , Santa Fe, NM 87501, USA
                [ 2 ] Complexity Science Hub Vienna, , 1080 Vienna, Austria
                [ 3 ] Vermont Complex Systems Center, University of Vermont, , Burlington, VM 05405, USA
                [ 4 ] South, Denmark, University, , Odense 5230, Denmark
                [ 5 ]School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195, USA
                [ 6 ] Department of Zoology, University of Oxford, , Oxford OX1 3PS, UK
                [ 7 ] Department of Mechanics, Mathematics and Management, Politecnico di Bari, , Bari 70125, Italy
                [ 8 ]Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
                [ 9 ]Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
                [ 10 ] Department of Mathematics, Max-Planck-Institute for Evolutionary Anthropology, , Leipzig 04103, Germany
                [ 11 ] Biology Department, University of Massachusetts Boston, , Boston, MA 02125, USA
                [ 12 ] Centre for Coevolution of Biology and Culture, Durham University, Anthropology Department, Durham, DH1 3LE, UK
                [ 13 ] Centre for Culture and Evolution, Division of Psychology, Brunel University London, , Uxbridge, UB8 3PH, UK
                [ 14 ]Department of Scientific Computing, Pukyong National University, 45 Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea
                [ 15 ]Department of Ecology and Conservation, University of Exeter, Penryn TR10 9FE, UK
                [ 16 ]New Jersey Institute of Technology, Newark, NJ 07102, USA
                [ 17 ]Department of Computer Science, University of Manchester, Manchester, M13 9PL, UK
                [ 18 ]Department of Cognitive and Information Sciences, University of California, Merced, CA 95343, USA
                [ 19 ]Department of Physics and Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, USA
                Author information
                http://orcid.org/0000-0002-1712-9455
                https://orcid.org/0000-0002-5057-0103
                http://orcid.org/0000-0002-3408-6274
                http://orcid.org/0000-0001-8357-8358
                http://orcid.org/0000-0002-6244-2918
                http://orcid.org/0000-0003-3766-6597
                http://orcid.org/0000-0001-8232-8365
                http://orcid.org/0000-0002-1998-6928
                http://orcid.org/0000-0002-7740-1625
                http://orcid.org/0000-0002-7133-5620
                Article
                rsif20220736
                10.1098/rsif.2022.0736
                10031425
                36946092
                ed6ecd39-2ceb-4006-bbe3-9df8c5709b77
                © 2023 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : October 8, 2022
                : Feburary 27, 2023
                Funding
                Funded by: NSF;
                Award ID: 1918490
                Award ID: BCS 1745154
                Award ID: DRMS 1757211
                Categories
                1004
                44
                70
                181
                Review Articles
                Review Articles

                Life sciences
                collective adaptation,collective intelligence,social networks,social cognition,computational models

                Comments

                Comment on this article