5 citations · 13 across the 7 of their papers we have counts for
5 papers · 1 filter
Robotic self-representation improves manipulation skills and transfer learning
Phuong D. H. Nguyen, Manfred Eppe, Stefan Wermter
Cognitive science suggests that the self-representation is critical for learning and problem-solving. However, there is a lack of computational methods that relate this claim to co…
Reinforcement Learning with Time-dependent Goals for Robotic Musicians
Thilo Fryen, Manfred Eppe, Phuong D. H. Nguyen +2
Reinforcement learning is a promising method to accomplish robotic control tasks. The task of playing musical instruments is, however, largely unexplored because it involves the ch…
Sensorimotor representation learning for an "active self" in robots: A model survey
Phuong D. H. Nguyen, Yasmin Kim Georgie, Ezgi Kayhan +3
Safe human-robot interactions require robots to be able to learn how to behave appropriately in \sout{humans' world} \rev{spaces populated by people} and thus to cope with the chal…
Enhancing a Neurocognitive Shared Visuomotor Model for Object Identification, Localization, and Grasping With Learning From Auxiliary Tasks
Matthias Kerzel, Fares Abawi, Manfred Eppe +1
We present a follow-up study on our unified visuomotor neural model for the robotic tasks of identifying, localizing, and grasping a target object in a scene with multiple objects.…
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…