This paper proposes a fully decentralized federated learning (FL) scheme for Internet of Everything (IoE) devices that are connected via multi-hop networks. Because FL algorithms hardly converge the parameters machine (ML) models, this focuses on convergence ML models in function spaces. Considering representative loss functions tasks e.g, mean squared error (MSE) and Kullback-Leibler (KL) dive...