2 papers
cs.LG2025
Fisher-Guided Selective Forgetting: Mitigating The Primacy Bias in Deep Reinforcement Learning
Massimiliano Falzari, Matthia Sabatelli
Deep Reinforcement Learning (DRL) systems often tend to overfit to early experiences, a phenomenon known as the primacy bias (PB). This bias can severely hinder learning efficiency…
cs.LG2024
Upside-Down Reinforcement Learning for More Interpretable Optimal Control
Juan Cardenas-Cartagena, Massimiliano Falzari, Marco Zullich +1
Model-Free Reinforcement Learning (RL) algorithms either learn how to map states to expected rewards or search for policies that can maximize a certain performance function. Model-…