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

2025/12/10 by Persson, Mika, Lidman, Jonas, Ljungberg, Jacob +2
#Artificial Intelligence (cs.AI) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Electrical engineering #Multiagent Systems (cs.MA) #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2512.09682

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.

Citations

• The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
• Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

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