5 citations · 12 across the 6 of their papers we have counts for
4 papers · 1 filter
Language-Conditioned Reinforcement Learning to Solve Misunderstandings with Action Corrections
Frank Röder, Manfred Eppe
Human-to-human conversation is not just talking and listening. It is an incremental process where participants continually establish a common understanding to rule out misunderstan…
Curious Hierarchical Actor-Critic Reinforcement Learning
Frank Röder, Manfred Eppe, Phuong D. H. Nguyen +1
Hierarchical abstraction and curiosity-driven exploration are two common paradigms in current reinforcement learning approaches to break down difficult problems into a sequence of…
From semantics to execution: Integrating action planning with reinforcement learning for robotic causal problem-solving
Manfred Eppe, Phuong D. H. Nguyen, Stefan Wermter
Reinforcement learning is an appropriate and successful method to robustly perform low-level robot control under noisy conditions. Symbolic action planning is useful to resolve cau…
Curriculum goal masking for continuous deep reinforcement learning
Manfred Eppe, Sven Magg, Stefan Wermter
Deep reinforcement learning has recently gained a focus on problems where policy or value functions are independent of goals. Evidence exists that the sampling of goals has a stron…