Journal article
Investigating the effects of robot engagement communication on learning from demonstration
- Abstract:
- Robot learning from demonstration (RLfD) is a technique for robots to derive policies from instructors’ examples. Although the reciprocal effects of student engagement on teacher behavior are widely recognized in the educational community, it is unclear whether the same phenomenon holds for RLfD. To fill this gap, we first design three types of robot engagement behavior (gaze, imitation, and a hybrid of the two) based on the learning literature. We then conduct, in a simulation environment, a within-subject user study to investigate the impact of different robot engagement cues on humans compared to a “without-engagement” condition. Results suggest that engagement communication has significantly negative influences on the human’s estimation of the simulated robots’ capability and significantly raises their expectation towards the learning outcomes, even though we do not run actual imitation learning algorithms in the experiments. Moreover, imitation behavior affects humans more than gaze does in all metrics, while their combination has the most profound influences on humans. We also find that communicating engagement via imitation or the combined behavior significantly improves humans’ perception towards the quality of simulated demonstrations, even if all demonstrations are of the same quality.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, 2.0MB, Terms of use)
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- Publisher copy:
- 10.1007/s12369-021-00825-2
Authors
- Publisher:
- Springer
- Journal:
- International Journal of Social Robotics More from this journal
- Volume:
- 14
- Issue:
- 3
- Pages:
- 789–806
- Publication date:
- 2021-10-08
- Acceptance date:
- 2021-08-30
- DOI:
- EISSN:
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1875-4805
- ISSN:
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1875-4791
- Language:
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English
- Keywords:
- Pubs id:
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1199295
- Local pid:
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pubs:1199295
- Deposit date:
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2021-10-07
Terms of use
- Copyright holder:
- Sun et al.
- Copyright date:
- 2021
- Rights statement:
- © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
- Licence:
- CC Attribution (CC BY)
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