Li-Jing Dong

Graph-Based Safe Reinforcement Learning for Multi-Agent Systems with Time-Varying Topology

A graph-based safe multi-agent reinforcement learning (MARL) framework for cooperative navigation with time-varying topology is presented, integrating a attention-based actor and a Graph Attention Network (GAT) centralized critic, enabling scale-insensitive policy learning under time-varying communication topologies.