FedMAGS applies GAT-Seq2Seq modeling inside a federated meta-RL loop to optimize offloading decisions for complex DAG tasks across distributed vehicular edge servers.
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Heterogeneous Tasks Offloading in Vehicular Edge Computing: A Federated Meta Deep Reinforcement Learning Approach
FedMAGS applies GAT-Seq2Seq modeling inside a federated meta-RL loop to optimize offloading decisions for complex DAG tasks across distributed vehicular edge servers.