Yang Zhao

Graph-Embedded En-Route Reinforcement Learning for Fine-Granularity Resource Orchestration in Computing Power Optical Networks

A Graph-Embedded En-Route Reinforcement Learning (GEERL) framework that efficiently encodes network topology into compact graph representations by exploiting topological correlations between structure and traffic patterns, enabling fast per-hop decisions without centralized planning overhead.