Name
Title | ||
|---|---|---|
Investigating Transparency Methods in a Robot Word-Learning System and Their Effects on Human Teaching Behaviors |
Abstract | ||
|---|---|---|
Robots need to understand words for references in social spaces (e.g., objects, locations, actions). Grounded language learning systems aim to learn these words from observing a human tutor. Teaching a robot is difficult for naive users due to the discrepancy between the users' mental model and the actual state of the robot. We present a grounded word-learning system with the Pepper robot which le... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/RO-MAN50785.2021.9515518 | 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) |
Keywords | DocType | ISSN |
Learning systems,Visualization,Statistical analysis,Education,Cognitive science,Robots | Conference | 1944-9445 |
ISBN | Citations | PageRank |
978-1-6654-0492-1 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthias Hirschmanner | 1 | 0 | 0.34 |
| Stephanie Gross | 2 | 0 | 2.37 |
| Setareh Zafari | 3 | 0 | 0.68 |
| Brigitte Krenn | 4 | 0 | 0.34 |
| Friedrich Neubarth | 5 | 0 | 0.34 |
| Markus Vincze | 6 | 0 | 0.34 |