Showing cs.LGShow all
2 papers · 1 filter
cs.LG2024
CANDID DAC: Leveraging Coupled Action Dimensions with Importance Differences in DAC
Philipp Bordne, M. Asif Hasan, Eddie Bergman +2
High-dimensional action spaces remain a challenge for dynamic algorithm configuration (DAC). Interdependencies and varying importance between action dimensions are further known ke…
cs.LG2024
Inferring Behavior-Specific Context Improves Zero-Shot Generalization in Reinforcement Learning
Tidiane Camaret Ndir, André Biedenkapp, Noor Awad
In this work, we address the challenge of zero-shot generalization (ZSG) in Reinforcement Learning (RL), where agents must adapt to entirely novel environments without additional t…