1 citations · 2 across the 8 of their papers we have counts for
9 papers
Teaching is a Process: The TOSS Framework for Modeling Human Teaching Decisions in Human-Interactive Robot Learning
Bernhard Hilpert, Kim Baraka, Joost Broekens
Successful Human-Robot Teaching assumes alignment between robot processing needs and human teaching intent. To better understand this alignment, this work seeks to uncover the unde…
Static Is Not Enough: A Comparative Study of VR and SpaceMouse in Static and Dynamic Teleoperation Tasks
Yijun Zhou, Muhan Hou, Kim Baraka
Imitation learning relies on high-quality demonstrations, and teleoperation is a primary way to collect them, making teleoperation interface choice crucial for the data. Prior work…
A Systematic Review of Human-AI Co-Creativity
Saloni Singh, Koen Hindriks, Dirk Heylen +1
The co creativity community is making significant progress in developing more sophisticated and tailored systems to support and enhance human creativity. Design considerations from…
Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes
Bernhard Hilpert, Muhan Hou, Kim Baraka +1
Reinforcement Learning (RL) agents often exhibit learning behaviors that are not intuitively interpretable by human observers, which can result in suboptimal feedback in collaborat…
Robot Policy Transfer with Online Demonstrations: An Active Reinforcement Learning Approach
Muhan Hou, Koen Hindriks, A. E. Eiben +1
Transfer Learning (TL) is a powerful tool that enables robots to transfer learned policies across different environments, tasks, or embodiments. To further facilitate this process,…
Active Robot Curriculum Learning from Online Human Demonstrations
Muhan Hou, Koen Hindriks, A. E. Eiben +1
Learning from Demonstrations (LfD) allows robots to learn skills from human users, but its effectiveness can suffer due to sub-optimal teaching, especially from untrained demonstra…
Prosody as a Teaching Signal for Agent Learning: Exploratory Studies and Algorithmic Implications
Matilda Knierim, Sahil Jain, Murat Han Aydoğan +4
Agent learning from human interaction often relies on explicit signals, but implicit social cues, such as prosody in speech, could provide valuable information for more effective l…
"Give Me an Example Like This": Episodic Active Reinforcement Learning from Demonstrations
Muhan Hou, Koen Hindriks, A. E. Eiben +1
Reinforcement Learning (RL) has achieved great success in sequential decision-making problems, but often at the cost of a large number of agent-environment interactions. To improve…
Fine-grained Affective Processing Capabilities Emerging from Large Language Models
Joost Broekens, Bernhard Hilpert, Suzan Verberne +3
Large language models, in particular generative pre-trained transformers (GPTs), show impressive results on a wide variety of language-related tasks. In this paper, we explore Chat…