IDEAS home Printed from https://ideas.repec.org/a/igg/jsir00/v1y2010i2p80-97.html
   My bibliography  Save this article

Honey Bee Swarm Cognition: Decision-Making Performance and Adaptation

Author

Listed:
  • Kevin M. Passino

    (Ohio State University, USA)

Abstract

A synthesis of findings from neuroscience, psychology, and behavioral biology has been recently used to show that several key features of cognition in neuron-based brains of vertebrates are also present in bee-based swarms of honey bees. Here, simulation tests are administered to the honey bee swarm cognition system to study its decision-making performance. First, tests are used to evaluate the ability of the swarm to discriminate between choice options and avoid picking inferior “distractor” options. Second, a “Treisman feature search test” from psychology, and tests of irrationality developed for humans, are administered to show that the swarm possesses some features of human decision-making performance. Evolutionary adaptation of swarm decision making is studied by administering swarm choice tests when there are variations on the parameters of the swarm’s decision-making mechanisms. The key result is that in addition to trading off decision-making speed and accuracy, natural selection seems to have settled on parameters that result in individual bee-level assessment noise being effectively filtered out to not adversely affect swarm-level decision-making performance.

Suggested Citation

  • Kevin M. Passino, 2010. "Honey Bee Swarm Cognition: Decision-Making Performance and Adaptation," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 1(2), pages 80-97, April.
  • Handle: RePEc:igg:jsir00:v:1:y:2010:i:2:p:80-97
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jsir.2010040105
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jsir00:v:1:y:2010:i:2:p:80-97. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.