3 papers
cs.LG2025
"So, Tell Me About Your Policy...": Distillation of interpretable policies from Deep Reinforcement Learning agents
Giovanni Dispoto, Paolo Bonetti, Marcello Restelli
Recent advances in Reinforcement Learning (RL) largely benefit from the inclusion of Deep Neural Networks, boosting the number of novel approaches proposed in the field of Deep Rei…
cs.LG2025
Gym4ReaL: A Suite for Benchmarking Real-World Reinforcement Learning
Davide Salaorni, Vincenzo De Paola, Samuele Delpero +9
In recent years, \emph{Reinforcement Learning} (RL) has made remarkable progress, achieving superhuman performance in a wide range of simulated environments. As research moves towa…
cs.LG2024
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance Analysis
Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli
Multi-task learning (MTL) is a powerful machine learning paradigm designed to leverage shared knowledge across tasks to improve generalization and performance. Previous works have…