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arXiv · 2512.09682

Dynamic one-time delivery of critical data by small and sparse UAV swarms: a model problem for MARL scaling studies

Mika Persson·Jonas Lidman·Jacob Ljungberg·Samuel Sandelius·Adam Andersson
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Abstract

This work studies the application of Multi-Agent Reinforcement Learning (MARL) to decentralized control of unmanned aerial vehicles to relay a critical data package to a known position. For this purpose, a family of deterministic games is introduced, designed for MARL scaling studies. A robust baseline policy is proposed which restricts agent motion and applies Dijkstra's shortest path algorithm. Computational experiment results show that two off-the-shelf MARL algorithms perform competitively with the baseline for a small number of agents, but face scalability issues as the number of agents increases. Source code and animations are available online at https://github.com/mikapersson/Information-Relaying.

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Mika Persson, Jonas Lidman, Jacob Ljungberg, Samuel Sandelius, Adam Andersson. 2025-12-10. Dynamic one-time delivery of critical data by small and sparse UAV swarms: a model problem for MARL scaling studies. https://arxiv.org/abs/2512.09682

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