Graph Neural Network-Aided Multi-Agent Reinforcement Learning for Efficient Wireless Communication

GNNComm-MARL leverages graph neural networks to enable efficient communication and collaboration among agents in multi-agent reinforcement learning systems, addressing challenges of partial observability, non-stationarity, and scalability in wireless communication networks.