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Game-based modeling of independent searchers who share a common goal

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  • Wettergren, Thomas A.

Abstract

We develop a mathematical model of the performance of a group of independent Bayesian searchers who are all seeking a common goal. In this context, the searchers do not directly interact with one another, but they may observe the behavior of nearby searchers and adjust their behavior accordingly. By modeling this system as an evolutionary game, an evolutionarily stable strategy is found for the percentage of time that a given searcher should bias its performance towards that of others vice when it should follow its own instincts. The dependence of the value of this equilibrium on the group size is determined. Numerical simulation experiments demonstrate the validity of the analytical results. The article concludes with a numerical assessment of the robustness of the stable strategy to a small number of deviating searchers, that is, searchers who adopt an alternative group following strategy.

Suggested Citation

  • Wettergren, Thomas A., 2021. "Game-based modeling of independent searchers who share a common goal," Applied Mathematics and Computation, Elsevier, vol. 391(C).
    • Handle: RePEc:eee:apmaco:v:391:y:2021:i:c:s0096300320305750
    DOI: 10.1016/j.amc.2020.125621
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    References listed on IDEAS

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    1. Ferdinandy, B. & Bhattacharya, K. & Ábel, D. & Vicsek, T., 2012. "Landing together: How flocks arrive at a coherent action in time and space in the presence of perturbations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1207-1215.
    2. Thomas A. Wettergren & John G. Baylog, 2014. "Discrete search allocation with object uncertainty," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 20(1), pages 1-20.
    3. Lidbetter, Thomas, 2013. "Search games with multiple hidden objects," LSE Research Online Documents on Economics 55103, London School of Economics and Political Science, LSE Library.
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    Cited by:

    1. Wettergren, Thomas A., 2021. "Replicator dynamics of an N-player snowdrift game with delayed payoffs," Applied Mathematics and Computation, Elsevier, vol. 404(C).

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