4 citations · 4 across the 1 of their papers we have counts for
4 papers
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…
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…
Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction
Manfred Eppe, Sean Trott, Jerome Feldman
We develop a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we em…