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Bi-stable collective states provide ants with multiple problem-solving strategies during cooperative transport
We investigate the dynamics of cooperative transport, where the motion of the ants is frustrated by an obstacle that contains a narrow opening that serves as the only available passage to the nest, and through which single ants can pass but not the cargo. A theoretical model for this frustrated motion predicts a bi-stable dynamic behavior that stochastically switches between large amplitude oscillations along the obstacle and extended lingering near the opening. These predictions are experimentally confirmed: The bi-stability provides two possible problem solving strategies, whereby the ants attempt to fit small objects through the opening, but guide large objects away from the opening and around the obstacle. Ron et al.
Image Credit: Ehud Fonio
Citation: (2018) PLoS Computational Biology Issue Image | Vol. 14(5) May 2018. PLoS Comput Biol 14(5): ev14.i05. https://doi.org/10.1371/image.pcbi.v14.i05
Published: May 31, 2018
Copyright: © 2018 Ofer Feinerman, Nir Gov, Jonathan Ron, and Ehud Fonio. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
We investigate the dynamics of cooperative transport, where the motion of the ants is frustrated by an obstacle that contains a narrow opening that serves as the only available passage to the nest, and through which single ants can pass but not the cargo. A theoretical model for this frustrated motion predicts a bi-stable dynamic behavior that stochastically switches between large amplitude oscillations along the obstacle and extended lingering near the opening. These predictions are experimentally confirmed: The bi-stability provides two possible problem solving strategies, whereby the ants attempt to fit small objects through the opening, but guide large objects away from the opening and around the obstacle. Ron et al.
Image Credit: Ehud Fonio