3 papers
q-fin.PM2026
Eliciting ESG Preferences for Reinforcement Learning-Based Portfolio Optimization
Giovanni Dispoto, Marcello Restelli, Carmine Ventre
Modern portfolio management increasingly demands a balance between traditional risk-adjusted returns and strict Environmental, Social, and Governance (ESG) mandates. Current Reinfo…
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…