Ants find shortest paths using simple, local rules

Chris R. Reid

doi:10.3758/s13420-023-00580-6

Ants find shortest paths using simple, local rules

Chris R. Reid^*

^*Corresponding author for this work

School of Natural Sciences

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	1-2
Number of pages	2
Journal	Learning and Behavior
Volume	52
Issue number	1
Early online date	17 Mar 2023
DOIs	https://doi.org/10.3758/s13420-023-00580-6
Publication status	Published - Mar 2024

Keywords

Collective behavior
Collective cognition
Optimization
Self-organization
Simulation modelling

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10.3758/s13420-023-00580-6

Cite this

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KW - Self-organization

KW - Simulation modelling

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Ants find shortest paths using simple, local rules

Abstract

Keywords

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