PRISM: Reinforced Semantic Communication for Decentralized Federated Anomaly Detection in Vehicular Networks
This work proposes Policy-driven Representation and Information Selection Method (PRISM), a Reinforcement Learning (RL)-based method that optimizes semantic communication in DFL through adaptive representation selection and intelligent topology management.
George Levis, Antonio Di Maio
· Proceedings of the Twenty-se... · 0 citations