Ant collective cognition allows for efficient navigation through disordered environments

  1. Aviram Gelblum
  2. Ehud Fonio
  3. Yoav Rodeh
  4. Amos Korman  Is a corresponding author
  5. Ofer Feinerman  Is a corresponding author
  1. Weizmann Institute of Science, Israel
  2. Ort Braude College, Israel
  3. CNRS and University of Paris, France

Abstract

The cognitive abilities of biological organisms only make sense in the context of their environment. Here, we study longhorn crazy ant collective navigation skills within the context of a semi-natural, randomized environment. Mapping this biological setting into the 'Ant-in-a-Labyrinth' framework which studies physical transport through disordered media allows us to formulate precise links between the statistics of environmental challenges and the ants' collective navigation abilities. We show that, in this environment, the ants use their numbers to collectively extend their sensing range. Although this extension is moderate, it nevertheless allows for extremely fast traversal times that overshadow known physical solutions to the 'Ant-in-a-Labyrinth' problem. To explain this large payoff, we use percolation theory and prove that whenever the labyrinth is solvable, a logarithmically small sensing range suffices for extreme speedup. Overall, our work demonstrates the potential advantages of group living and collective cognition in increasing a species' habitable range.

Data availability

Full raw data of both the labyrinths and the ants collective trajectories through these labyrinths were uploaded with this submission.

Article and author information

Author details

  1. Aviram Gelblum

    Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
    Competing interests
    The authors declare that no competing interests exist.
  2. Ehud Fonio

    Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
    Competing interests
    The authors declare that no competing interests exist.
  3. Yoav Rodeh

    Department of Software Engineering, Ort Braude College, Karmiel, Israel
    Competing interests
    The authors declare that no competing interests exist.
  4. Amos Korman

    The Research Institute on the Foundations of Computer Science (IRIF), CNRS and University of Paris, Paris, France
    For correspondence
    amos.korman@irif.fr
    Competing interests
    The authors declare that no competing interests exist.
  5. Ofer Feinerman

    Department of Physics of Complex Systems, Weizmann Institute of Science, Rehobot, Israel
    For correspondence
    ofer.feinerman@weizmann.ac.il
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4145-0238

Funding

Horizon 2020 Framework Programme (770964)

  • Ofer Feinerman

Horizon 2020 Framework Programme (648032)

  • Amos Korman

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Gordon J Berman, Emory University, United States

Version history

  1. Received: January 15, 2020
  2. Accepted: May 2, 2020
  3. Accepted Manuscript published: May 12, 2020 (version 1)
  4. Accepted Manuscript updated: May 14, 2020 (version 2)
  5. Version of Record published: July 2, 2020 (version 3)

Copyright

© 2020, Gelblum et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Aviram Gelblum
  2. Ehud Fonio
  3. Yoav Rodeh
  4. Amos Korman
  5. Ofer Feinerman
(2020)
Ant collective cognition allows for efficient navigation through disordered environments
eLife 9:e55195.
https://doi.org/10.7554/eLife.55195

Share this article

https://doi.org/10.7554/eLife.55195

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