activity
20182026
most citedIntelligent problem-solving as integrated hierarchical reinforcement learning

93 citations · 123 across the 28 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

cs.AI2020

Hierarchical principles of embodied reinforcement learning: A review

Manfred Eppe, Christian Gumbsch, Matthias Kerzel +3

Cognitive Psychology and related disciplines have identified several critical mechanisms that enable intelligent biological agents to learn to solve complex problems. There exists…

cs.CV2020★ 4 cited

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.…

cs.NE2020

Crossmodal Language Grounding in an Embodied Neurocognitive Model

Stefan Heinrich, Yuan Yao, Tobias Hinz +5

Human infants are able to acquire natural language seemingly easily at an early age. Their language learning seems to occur simultaneously with learning other cognitive functions a…

cs.RO2020

Explainable Goal-Driven Agents and Robots -- A Comprehensive Review

Fatai Sado, Chu Kiong Loo, Wei Shiung Liew +2

Recent applications of autonomous agents and robots, such as self-driving cars, scenario-based trainers, exploration robots, and service robots have brought attention to crucial tr…

cs.LG2020

Improving Robot Dual-System Motor Learning with Intrinsically Motivated Meta-Control and Latent-Space Experience Imagination

Muhammad Burhan Hafez, Cornelius Weber, Matthias Kerzel +1

Combining model-based and model-free learning systems has been shown to improve the sample efficiency of learning to perform complex robotic tasks. However, dual-system approaches…