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Cited by 558

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Explorations in engagement for humans and robots

Open access
Sidner, Candace L., Lee, Christopher, Kidd, Cory D., Lesh, Neal, Rich, Charles·2005·Artificial Intelligence

Abstract

This paper explores the concept of engagement, the process by which individuals in an interaction start, maintain and end their perceived connection to one another. The paper reports on one aspect of engagement among human interactors--the effect of tracking faces during an interaction. It also describes the architecture of a robot that can participate in conversational, collaborative interactions with engagement gestures. Finally, the paper reports on findings of experiments with human participants who interacted with a robot when it either performed or did not perform engagement gestures. Results of the human-robot studies indicate that people become engaged with robots: they direct their attention to the robot more often in interactions where engagement gestures are present, and they find interactions more appropriate when engagement gestures are present than when they are not.

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Registry

Crossref · 10.1016/j.artint.2005.03.005

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Metadata

Authors
Sidner, C. L., Lee, C., Kidd, C. D., Lesh, N., & Rich, C.
Venue
Artificial Intelligence
Publisher
Elsevier BV
Published
2005-08
Volume
166
Issue
1-2
Pages
140-164
ISSN
0004-3702 (ISSN-L)
OpenAlex
W2096284813
Cited by
558
References
47
FWCI
28.39
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Explorations in engagement for humans and robots. https://app.cochat.ai/papers/10.1016/j.artint.2005.03.005
The paper
Sidner, C. L., Lee, C., Kidd, C. D., Lesh, N., & Rich, C. (2005). Explorations in engagement for humans and robots. Artificial Intelligence. https://doi.org/10.1016/j.artint.2005.03.005

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.