8 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…