Blog
About

5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Costs of task allocation with local feedback: Effects of colony size and extra workers in social insects and other multi-agent systems

      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

          Adaptive collective systems are common in biology and beyond. Typically, such systems require a task allocation algorithm: a mechanism or rule-set by which individuals select particular roles. Here we study the performance of such task allocation mechanisms measured in terms of the time for individuals to allocate to tasks. We ask: (1) Is task allocation fundamentally difficult, and thus costly? (2) Does the performance of task allocation mechanisms depend on the number of individuals? And (3) what other parameters may affect their efficiency? We use techniques from distributed computing theory to develop a model of a social insect colony, where workers have to be allocated to a set of tasks; however, our model is generalizable to other systems. We show, first, that the ability of workers to quickly assess demand for work in tasks they are not currently engaged in crucially affects whether task allocation is quickly achieved or not. This indicates that in social insect tasks such as thermoregulation, where temperature may provide a global and near instantaneous stimulus to measure the need for cooling, for example, it should be easy to match the number of workers to the need for work. In other tasks, such as nest repair, it may be impossible for workers not directly at the work site to know that this task needs more workers. We argue that this affects whether task allocation mechanisms are under strong selection. Second, we show that colony size does not affect task allocation performance under our assumptions. This implies that when effects of colony size are found, they are not inherent in the process of task allocation itself, but due to processes not modeled here, such as higher variation in task demand for smaller colonies, benefits of specialized workers, or constant overhead costs. Third, we show that the ratio of the number of available workers to the workload crucially affects performance. Thus, workers in excess of those needed to complete all tasks improve task allocation performance. This provides a potential explanation for the phenomenon that social insect colonies commonly contain inactive workers: these may be a ‘surplus’ set of workers that improves colony function by speeding up optimal allocation of workers to tasks. Overall our study shows how limitations at the individual level can affect group level outcomes, and suggests new hypotheses that can be explored empirically.

          Author summary

          Many complex systems have to allocate their units to different functions: cells in an embryo develop into different tissues, servers in a computer cluster perform different calculations, and insect workers choose particular tasks, such as brood care or foraging. Here we demonstrate that this process does not automatically become easier or harder with system size. If more workers are present than needed to complete the work available, some workers will always be idle; despite this, having surplus workers makes redistributing them across the tasks that need work much faster. Thus, unexpectedly, such surplus, idle workers may potentially significantly improve system performance. Our work suggests that interdisciplinary studies between biology and distributed computing can yield novel insights for both fields.

          Related collections

          Most cited references 72

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

          Notch signaling: cell fate control and signal integration in development.

          Notch signaling defines an evolutionarily ancient cell interaction mechanism, which plays a fundamental role in metazoan development. Signals exchanged between neighboring cells through the Notch receptor can amplify and consolidate molecular differences, which eventually dictate cell fates. Thus, Notch signals control how cells respond to intrinsic or extrinsic developmental cues that are necessary to unfold specific developmental programs. Notch activity affects the implementation of differentiation, proliferation, and apoptotic programs, providing a general developmental tool to influence organ formation and morphogenesis.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Regulation of division of labor in insect societies.

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

              The Insect Societies

                Bookmark

                Author and article information

                Affiliations
                [1 ] Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, USA
                [2 ] Department of Ecology and Evolutionary Biology, The University of Arizona, Tucson, AZ, USA
                [3 ] School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
                University of California Irvine, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                ‡ These authors are joint senior authors on this work.

                Contributors
                ORCID: http://orcid.org/0000-0001-7179-0706, Role: Conceptualization, Role: Formal analysis, Role: Methodology, Role: Writing – original draft
                Role: Conceptualization, Role: Funding acquisition, Role: Methodology, Role: Project administration, Role: Supervision, Role: Writing – review & editing
                ORCID: http://orcid.org/0000-0003-3045-265X, Role: Conceptualization, Role: Formal analysis, Role: Funding acquisition, Role: Methodology, Role: Project administration, Role: Supervision, Role: Writing – review & editing
                ORCID: http://orcid.org/0000-0001-9756-0167, Role: Conceptualization, Role: Funding acquisition, Role: Methodology
                Role: Conceptualization, Role: Formal analysis, Role: Methodology
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                December 2017
                14 December 2017
                : 13
                : 12
                PCOMPBIOL-D-17-00494
                10.1371/journal.pcbi.1005904
                5746283
                29240763
                © 2017 Radeva et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Counts
                Figures: 2, Tables: 4, Pages: 29
                Product
                Funding
                Funded by: Wyss Institute for Biologically Inspired Engineering, Harvard University
                Award Recipient : ORCID: http://orcid.org/0000-0001-9756-0167
                Funded by: funder-id http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: CCF-0939370
                Award Recipient : ORCID: http://orcid.org/0000-0003-3045-265X
                Funded by: funder-id http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: CCF-1461559
                Award Recipient : ORCID: http://orcid.org/0000-0003-3045-265X
                Funded by: funder-id http://dx.doi.org/10.13039/100006831, U.S. Air Force;
                Award ID: FA9550-13-1-0042
                Award Recipient : ORCID: http://orcid.org/0000-0003-3045-265X
                Funded by: funder-id http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: IOS-3014230
                Award Recipient :
                RN is funded by the Wyss Institute for Biologically Inspired Engineering, Harvard University ( https://wyss.harvard.edu/). AD is funded by the National Science Foundation ( https://www.nsf.gov/) Awards number IOS-3014230. NL, TR, and HS are funded by the National Science Foundation ( https://www.nsf.gov/) Awards numbers CCF-0939370 and CCF-1461559, and by the Air Force Office of Scientific Research ( http://www.wpafb.af.mil/afrl/afosr) Contract Number: FA9550-13-1-0042. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Social Sciences
                Sociology
                Social Systems
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Physical Sciences
                Mathematics
                Numerical Analysis
                Biology and Life Sciences
                Behavior
                Animal Behavior
                Foraging
                Biology and Life Sciences
                Zoology
                Animal Behavior
                Foraging
                Computer and Information Sciences
                Systems Science
                Complex Systems
                Physical Sciences
                Mathematics
                Systems Science
                Complex Systems
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Hymenoptera
                Bees
                Honey Bees
                Physical Sciences
                Mathematics
                Probability Theory
                Probability Distribution
                Custom metadata
                vor-update-to-uncorrected-proof
                2017-12-28
                All relevant data are within the paper and its Supporting Information files.

                Quantitative & Systems biology

                Comments

                Comment on this article