AI RESEARCH
Network Distributed Multi-Agent Reinforcement Learning for Consensus Control of Quadcopters
arXiv CS.AI
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ArXi:2606.02107v1 Announce Type: cross This paper proposes a Network Distributed Multi-Agent Reinforcement Learning (ND-MARL) framework for quadcopter consensus control. Compared to conventional multi-agent MARL formulations that rely on centralized planning or fully decentralized execution, ND-MARL incorporates the swarm communication graph into the decision process. Under a 2-Neighbor communication topology, each agent observes information of only two neighbors and outputs an action through a distributed policy.