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 Temnothorax ants. Each ant is modeled as a probabili...

Full description

Bibliographic Details
Main Authors: Zhang, Emily (Author), Zhao, Jiajia (Author), Lynch, Nancy (Author)
Format: Article
Language:English
Published: Mary Ann Liebert Inc, 2022-08-10T15:13:24Z.
Subjects:
Online Access:Get fulltext
Description
Summary: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 Temnothorax ants. Each ant is modeled as a probabilistic agent with limited power, and there is no central control governing the ants. We show an Ω(logn) lower bound on the running time of our proposed house-hunting algorithm, where n is the number of ants. Furthermore, we show a matching upper bound of expected O(logn) 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.