机译:FedKL: Tackling Data Heterogeneity in Federated Reinforcement Learning by Penalizing KL Divergence
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Sai kung, Hong Kong;
Training; Convergence; Data models; Servers; Heuristic algorithms; Optimization; Linear programming;