The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Infant-like Social Interactions between a Robot and a Human Caregiver
Abstract
From birth, human infants are immersed in a social environment that allows them to learn by leveraging the skills and capabilities of their caregivers. A critical pre-cursor to this type of social learning is the ability to maintain interaction levels that are neither overwhelming nor under-stim ulating. In this paper, we present a mechanism for an autonomous robot to regulate the intensity of its social interactions with a human. Similar to the feedback from infant to caregiver, the robot uses expressive displays to modulate the interaction intensity. This mechanism is integrated within a general framework that combines perception, attention, drives, emotions, behavior selection, and motor acts. We present a specific implementation of this architecture that enables the robot to react appropriately to both social stimuli (faces) and non-social stimuli (moving toys) while maintaining a suitable interaction intensity. We present results from both face-to-face interactions and interactions mediated through a toy. Note: This paper was submitted in June, 1998.
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Cites
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“Furthermore, parents use their infant’s display of excitement or interest as cues to regulate their interaction with them (Wood et al. 1976).”
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Cited by
Human–Robot Interaction: A Survey
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Emotion and sociable humanoid robots
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Self-citationTaxonomy of Risks posed by Language Models
Weidinger, L., Uesato, J., Rauh, M., Griffin, C., Huang, P.-S., Mellor, J., Glaese, A., Cheng, M., Balle, B., Kasirzadeh, A., et al. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3531146.3533088 · Cited by 764
“Similarly, in other interactive technologies it was found that the more human-like a system appears, the more likely it is that users attribute more human traits and capabilities to that system [29, 126, 208].”
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The Cog Project: Building a Humanoid Robot
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Metadata
- Authors
- Breazeal, C., & Scassellati, B.
- Venue
- Adaptive Behavior
- Publisher
- SAGE Publications
- Published
- 2000-01
- Volume
- 8
- Issue
- 1
- Pages
- 49-74
- ISSN
- 1059-7123 (ISSN-L)
- 1741-2633
- OpenAlex
- W1980882881
- Cited by
- 327
- References
- 39
- FWCI
- 37.95
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
