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
12/10/2025
eess.SYcs.AIcs.GT

No official code found. Best implementation: mikapersson/Information-Relaying (2 stars, last commit 2026-02-02).

Abstract

This work presents a conceptual study on the application of Multi-Agent Reinforcement Learning (MARL) for 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 scaling studies for MARL. A robust baseline policy is proposed, which is based on restricting agent motion envelopes and applying Dijkstra's algorithm. Experimental results show that two off-the-shelf MARL algorithms perform competitively with the baseline for a small number of agents, but scalability issues arise as the number of agents increase.

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Code Implementations(1)

mikapersson/Information-RelayingCommunity71%

Code for the MARL experiments and baseline from the paper "Dynamic one-time delivery of critical data by small and sparse UAV swarms: a model problem for MARL scaling studies"

21Python, Jupyter NotebookNov 15, 20248 months ago
paper

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Cite this paper

@article{persson2025dynamic,
  title  = {Dynamic one-time delivery of critical data by small and sparse UAV swarms: a model problem for MARL scaling studies},
  author = {Mika Persson and Jonas Lidman and Jacob Ljungberg and Samuel Sandelius and Adam Andersson},
  year   = {2025},
  eprint = {2512.09682},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.09682v1}
}

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