Abstract: A system for decentralized federated learning is provided. The system comprises agents and aggregators coupled to a communication network. Each agent comprises a data collector collecting raw data; a memory storing the collected raw data and a local machine learning model; and a processor training the local machine learning model. Each aggregator comprises a model collector collecting the local machine learning models; a memory storing the collected local machine learning models; and a processor creating a cluster machine learning model from the local machine learning models. The aggregators communicate with each other and exchange the cluster machine learning models to create a semi-global machine learning model. Each of the aggregators sends the semi-global machine learning model to the associated agents. Each of the agents updates the local machine learning model with the semi-global machine learning model.