Optimal and Resilient Pheromone Utilization in Ant Foraging
Yehuda Afek, Roman Kecher, Moshe Sulamy

TL;DR
This paper establishes the minimal pheromone amounts needed for ant-like agents to reliably find a hidden food source, providing optimal algorithms that are resilient to agent failures and applicable in both synchronous and asynchronous models.
Contribution
It introduces tight lower bounds on pheromone usage for FSM and Turing Machine modeled ants, along with optimal, fault-tolerant algorithms for deterministic foraging.
Findings
Lower bound of Ω(D) pheromones for FSM ants
Lower bound of Ω(k) pheromones for TM ants
Fault-tolerant algorithms with optimal pheromone and time complexity
Abstract
Pheromones are a chemical substance produced and released by ants as means of communication. In this work we present the minimum amount of pheromones necessary and sufficient for a colony of ants (identical mobile agents) to deterministically find a food source (treasure), assuming that each ant has the computational capabilities of either a Finite State Machine (FSM) or a Turing Machine (TM). In addition, we provide pheromone-based foraging algorithms capable of handling fail-stop faults. In more detail, we consider the case where identical ants, initially located at the center (nest) of an infinite two-dimensional grid and communicate only through pheromones, perform a collaborative search for an adversarially hidden treasure placed at an unknown distance . We begin by proving a tight lower bound of on the amount of pheromones required by any number of FSM based…
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