On Optimal Decision-Making in Ant Colonies

TL;DR

This paper enhances a mathematical model of ant colony decision-making by incorporating nest size information, aiming to explain how colonies achieve optimal choices during house-hunting.

Contribution

It introduces a modified model that includes nest size data, aligning theoretical predictions with laboratory observations of optimal decision-making.

Findings

Model with nest size info predicts optimality

Revised differential equations match lab results

Proposes testing strategy for the new model

Abstract

Colonies of ants can collectively choose the best of several nests, even when many of the active ants who organize the move visit only one site. Understanding such a behavior can help us design efficient distributed decision making algorithms. Marshall et al. propose a model for house-hunting in colonies of ant Temnothorax albipennis. Unfortunately, their model does not achieve optimal decision-making while laboratory experiments show that, in fact, colonies usually achieve optimality during the house-hunting process. In this paper, we argue that the model of Marshall et al. can achieve optimality by including nest size information in their mathematical model. We use lab results of Pratt et al. to re-define the differential equations of Marshall et al. Finally, we sketch our strategy for testing the optimality of the new model.