An Upper and Lower Bound for the Convergence Time of House-Hunting in Temnothorax Ant Colonies

We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by ants. Each ant is modeled as a probabilistic agent w...

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Veröffentlicht in:Journal of computational biology Jg. 29; H. 4; S. 344
Hauptverfasser: Zhang, Emily, Zhao, Jiajia, Lynch, Nancy
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 01.04.2022
Schlagworte:
Animals
Ants
Appetitive Behavior
Decision Making
Nesting Behavior
Social Behavior
convergence time
ant colony
decision-making
collective behavior
ISSN:1557-8666, 1557-8666
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Zusammenfassung:We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by ants. Each ant is modeled as a probabilistic agent with limited power, and there is no central control governing the ants. We show an lower bound on the running time of our proposed house-hunting algorithm, where is the number of ants. Furthermore, we show a matching upper bound of expected rounds for environments with only one candidate nest for the ants to move to. Our work provides insights into the house-hunting process, giving a perspective on how environmental factors such as nest quality or a quorum rule can affect the emigration process.
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ISSN:1557-8666
1557-8666
DOI:10.1089/cmb.2021.0364