We conducted a comprehensive tracking study of 64 unmarked ants within the same arena to examine the dynamics of individual behaviors within a collective, aiming to understand the underlying mechanisms that drive the colony's collective behaviors. Specifically, we analyzed the movement patterns of the ants to identify the “algorithm” governing their actions. One such approach we employed is the ϵ-machine method, pioneered by Crutchfield and colleagues, which predicts motion using a stochastic finite state machine. The results of our study revealed that individual ants exhibited either deterministic or stochastic behaviors, contingent upon their roles within the colony. Ants contributing to cluster formation displayed deterministic behaviors, whereas those exploring outside of the cluster were more likely to demonstrate stochastic behaviors.

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General Conference
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© 2023 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
2023
Massachusetts Institute of Technology
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Issue Section:
General Conference