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Adversarial Diffusion for Robust Reinforcement Learning
Daniele Foffano, Alessio Russo, Alexandre Proutiere
Robustness to modeling errors and uncertainties remains a central challenge in reinforcement learning (RL). In this work, we address this challenge by leveraging diffusion models t…
Explainable Reinforcement Learning via Temporal Policy Decomposition
Franco Ruggeri, Alessio Russo, Rafia Inam +1
We investigate the explainability of Reinforcement Learning (RL) policies from a temporal perspective, focusing on the sequence of future outcomes associated with individual action…
Offline Reinforcement Learning and Sequence Modeling for Downlink Link Adaptation
Samuele Peri, Alessio Russo, Gabor Fodor +1
Link adaptation (LA) is an essential function in modern wireless communication systems that dynamically adjusts the transmission rate of a communication link to match time- and fre…