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cs.LG2025
Deep SPI: Safe Policy Improvement via World Models
Florent Delgrange, Raphael Avalos, Willem Röpke
Safe policy improvement (SPI) offers theoretical control over policy updates, yet existing guarantees largely concern offline, tabular reinforcement learning (RL). We study SPI in…
cs.LG2024
Scalable Multi-Objective Reinforcement Learning with Fairness Guarantees using Lorenz Dominance
Dimitris Michailidis, Willem Röpke, Diederik M. Roijers +2
Multi-Objective Reinforcement Learning (MORL) aims to learn a set of policies that optimize trade-offs between multiple, often conflicting objectives. MORL is computationally more…