A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication

ArXi:2604.25972v1 Announce Type: cross In multi-agent reinforcement learning (MARL), the integration of a communication mechanism, allowing agents to better learn to coordinate their actions and converge on their objectives by sharing information. Based on an interaction graph, a subclass of methods employs graph neural networks (GNNs) to learn the communication, enabling agents to improve their internal representations by enriching them with information exchanged.