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A model for cooperative scientific research inspired by the ant colony algorithm

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  • Zhuoran He
  • Tingtao Zhou

Abstract

Modern scientific research has become largely a cooperative activity in the Internet age. We build a simulation model to understand the population-level creativity based on the heuristic ant colony algorithm. Each researcher has two heuristic parameters characterizing the goodness of his own judgments and his trust on literature. We study how the distributions of contributor heuristic parameters change with the research problem scale, stage of the research problem, and computing power available. We also identify situations where path dependence and hasty research due to the pressure on productivity can significantly impede the long-term advancement of scientific research. Our work provides some preliminary understanding and guidance for the dynamical process of cooperative scientific research in various disciplines.

Suggested Citation

  • Zhuoran He & Tingtao Zhou, 2022. "A model for cooperative scientific research inspired by the ant colony algorithm," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-11, January.
    • Handle: RePEc:plo:pone00:0262933
    DOI: 10.1371/journal.pone.0262933
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    References listed on IDEAS

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    1. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    2. Kim Holmberg & Mike Thelwall, 2014. "Disciplinary differences in Twitter scholarly communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1027-1042, November.
    3. Richard C. Larson & Navid Ghaffarzadegan & Yi Xue, 2014. "Too Many PhD Graduates or Too Few Academic Job Openings: The Basic Reproductive Number R0 in Academia," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(6), pages 745-750, November.
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