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Learning & Behavior

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17-03-2023 | Outlook

Ants find shortest paths using simple, local rules

Author: Chris R. Reid

Published in: Learning & Behavior | Issue 1/2024

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Garg et al. (2023, Proceedings of the National Academy of Sciences, 120[6], e2207959120) build simulation models to understand how turtle ants collectively find efficient paths through branched networks, highlighting the importance of bidirectional traffic, leakage of ants at junctions, and the ability to increase flow as key components for efficiency. Their findings provide new, biologically realistic mechanisms that could improve applications in our own engineered networks.

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Beekman, M., Sumpter, D. J., & Ratnieks, F. L. (2001). Phase transition between disordered and ordered foraging in Pharaoh’s ants. Proceedings of the National Academy of Sciences, 98(17), 9703–9706.ADSCrossRef

Chandrasekhar, A., Marshall, J. A., Austin, C., Navlakha, S., & Gordon, D. M. (2021). Better tired than lost: Turtle ant trail networks favor coherence over short edges. PLOS Computational Biology, 17(10), e1009523.ADSCrossRefPubMedPubMedCentral

Dorigo, M., & Stützle, T. (2019). Ant colony optimization: Overview and recent advances (pp. 311–351). Springer International Publishing.

Garg, S., Shiragur, K., Gordon, D. M., & Charikar, M. (2023). Distributed algorithms from arboreal ants for the shortest path problem. Proceedings of the National Academy of Sciences, 120(6), e2207959120.MathSciNetCrossRef

Title: Ants find shortest paths using simple, local rules
Author: Chris R. Reid
Publication date: 17-03-2023
Publisher: Springer US
Published in: Learning & Behavior / Issue 1/2024
Print ISSN: 1543-4494
Electronic ISSN: 1543-4508
DOI: https://doi.org/10.3758/s13420-023-00580-6

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