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Decentralized learning enhances privacy, scalability, and fault tolerance by  distributing data and computation across nodes. A popular approach is Federated learning, which relies on a [...]

Abstract Many network control problems (e.g., minimizing age-of-information, network slicing, and caching, just to name a few examples) can be cast as Markov Decision Processes [...]