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The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy

View ORCID ProfileClaudia Winklmayr, Albert B. Kao, Joseph B. Bak-Coleman, Pawel Romanczuk
doi: https://doi.org/10.1101/2020.01.09.899054
Claudia Winklmayr
Bernstein Center for Computational Neuroscience, Berlin, GermanyMax-Planck-Institut für Mathematik in den Naturwissenschaften, Leipzig, Germany
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  • ORCID record for Claudia Winklmayr
  • For correspondence: albert.kao@gmail.com claudia.winklmayr@mis.mpg.de
Albert B. Kao
Santa Fe Institute, Santa Fe, NM, USA
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  • For correspondence: albert.kao@gmail.com claudia.winklmayr@mis.mpg.de
Joseph B. Bak-Coleman
Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
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Pawel Romanczuk
Bernstein Center for Computational Neuroscience, Berlin, GermanyInstitute for Theoretical Biology, Department of Biology, Humboldt Universität zu Berlin, Germany
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ABSTRACT

Groups of organisms, from bacteria to fish schools to human societies, depend on their ability to make accurate decisions in an uncertain world. Most models of collective decision-making assume that groups reach a consensus during a decision-making bout, often through simple majority rule. In many natural and sociological systems, however, groups may fail to reach consensus, resulting in stalemates. Here, we build on opinion dynamics and collective wisdom models to examine how stalemates may affect the wisdom of crowds. For simple environments, where individuals have access to independent sources of information, we find that stalemates improve collective accuracy by selectively filtering out incorrect decisions. In complex environments, where individuals have access to both shared and independent information, this effect is even more pronounced, restoring the wisdom of crowds in regions of parameter space where large groups perform poorly when making decisions using majority rule. We identify network properties that tune the system between consensus and accuracy, providing mechanisms by which animals, or evolution, could dynamically adjust the collective decision-making process in response to the reward structure of the possible outcomes. Overall, these results highlight the adaptive potential of stalemale filtering for improving the decision-making abilities of group-living animals.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted January 10, 2020.
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The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy
Claudia Winklmayr, Albert B. Kao, Joseph B. Bak-Coleman, Pawel Romanczuk
bioRxiv 2020.01.09.899054; doi: https://doi.org/10.1101/2020.01.09.899054
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The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy
Claudia Winklmayr, Albert B. Kao, Joseph B. Bak-Coleman, Pawel Romanczuk
bioRxiv 2020.01.09.899054; doi: https://doi.org/10.1101/2020.01.09.899054

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