Sharing Experiences to Help a Robot Present Its Mind and Sociability
Bibliographic Data
| ID | 8104804 |
|---|---|
| Authors | Changzeng Fu (0000-0003-1083-9486, corresponding author), Yuichiro Yoshikawa (0000-0002-3484-0361), Takamasa Iio (0000-0002-6276-3316), Hiroshi Ishiguro (0000-0002-0805-7648) |
| Year | 2020 |
| Volume | 13 |
| Issue | 2 |
| Pages | 341-352 |
| Publication date | 2020-03-20 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Social Robotics (JOURNAL) |
| Journal identifiers | ISSN: 1875-4791 • E-ISSN: 1875-4805 |
| Publisher | Springer Science+Business Media (PUBLISHER • DE) |
| DOI | 10.1007/s12369-020-00643-y |
| OpenAlex | W3011041981 |
| Language | EN |
| Citations received | 6 |
| References cited | 30 |
Many social robots have emerged in public places to serve people. For these services, the robots are assumed to be able to present internal aspects (i.e., mind, sociability) to engage and interact with people over the long term. In this paper, we propose a novel dialogue structure called experience-based dialogue to help a robot present and maintain a good interaction over the long term. This dialogue structure contains a piece of knowledge and a story about how the robot gained this knowledge, which are used to compose the robot’s experience-related utterances for sharing experiences of interacting with previous users other than just the current user and help it present its internal aspects. We conducted an experiment to test the effects of our proposed dialogue structure and measure them with some published subjective scales. The results showed that experience-based dialogue can help a robot obtain better evaluations in terms of perceived intelligence, sociability, mind, anthropomorphism, animacy, likability, level of acceptance, and positive user reaction
Animacy · Cognitive psychology · Human–computer interaction · Knowledge management · Mobile robot · Robot · Robot control · Robotics · Social robot · Term (time · AI in Service Interactions · Computer Science · Multimodal Machine Learning Applications · Psychology · Social Robot Interaction and HRI · Artificial Intelligence · Social Psychology
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| Unique citing works | 6 |
|---|---|
| Citations per year | 1,5 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 6 |