Abstract

The solution of complex problems by the collective action of simple agents in both biologically evolved and synthetically engineered systems involves cooperative action. Understanding the resulting emergent solutions requires integrating across the organismal behaviors of many individuals. Here we investigate an ecologically relevant collective task in black carpenter ants Camponotus pennsylvanicus: excavation of a soft, erodible confining corral. Individual ants show a transition from individual exploratory excavation at random locations to spatially localized collective exploitative excavation and eventual excavate out from the corral. An agent minimal continuum theory that coarse-grains over individual actions and considers their integrated influence on the environment leads to the emergence of an effective phase space of behaviors in terms of excavation strength and cooperation intensity. To test the theory over the range of both observed and predicted behaviors, we used custom-built robots (RAnts) that respond to stimuli to characterize the phase space of emergence (and failure) of cooperative excavation. By tuning the amount of cooperation between RAnts, we found that we could vary the efficiency of excavation and synthetically generate the other macroscopic phases predicted by our theory. Overall, our approach shows how the cooperative completion of tasks can arise from simple rules that involve the interaction of agents with a dynamically changing environment that serves as both an enabler and a modulator of behavior.

Data availability

All the data used to generate the figures in the article are available here: https://github.com/sgangaprasath/rantIFigDataThe simulation code used in the article is also available in the same folder.

Article and author information

Author details

  1. S Ganga Prasath

    Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4545-911X
  2. Souvik Mandal

    Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9552-5613
  3. Fabio Giardina

    Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Jordan Kennedy

    Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Venkatesh N Murthy

    Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2443-4252
  6. L Mahadevan

    Harvard University, Cambridge, United States
    For correspondence
    lmahadev@g.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5114-0519

Funding

National Science Foundation (PHY1606895,1764269)

  • L Mahadevan

Henri Seydoux Fund

  • L Mahadevan

National Science Foundation (PHY1606895)

  • S Ganga Prasath

Swiss National Science Foundation

  • Fabio Giardina

Kavli Institute for Bionano Science and Technology

  • Souvik Mandal
  • Venkatesh N Murthy

Ford Foundation

  • Jordan Kennedy

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

Reviewing Editor

  1. Irene Giardina, Università Sapienza, Italy

Version history

  1. Preprint posted: July 12, 2021 (view preprint)
  2. Received: April 20, 2022
  3. Accepted: October 7, 2022
  4. Accepted Manuscript published: October 10, 2022 (version 1)
  5. Version of Record published: February 2, 2023 (version 2)

Copyright

© 2022, Prasath 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. S Ganga Prasath
  2. Souvik Mandal
  3. Fabio Giardina
  4. Jordan Kennedy
  5. Venkatesh N Murthy
  6. L Mahadevan
(2022)
Dynamics of cooperative excavation in ant and robot collectives
eLife 11:e79638.
https://doi.org/10.7554/eLife.79638

Share this article

https://doi.org/10.7554/eLife.79638

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