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Autor:
Mak, Hei Yi, Fan, Flint Xiaofeng, Lanzendörfer, Luca A., Tan, Cheston, Ooi, Wei Tsang, Wattenhofer, Roger
In this study, we delve into Federated Reinforcement Learning (FedRL) in the context of value-based agents operating across diverse Markov Decision Processes (MDPs). Existing FedRL methods typically aggregate agents' learning by averaging the value f
Externí odkaz:
http://arxiv.org/abs/2403.20156
