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Cited by 170

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Function Meets Style: Insights From Emotion Theory Applied to HRI

Breazeal, C.·2004·IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)

Abstract

As robot designers, we tend to emphasize the cognitive aspect of intelligence when designing robot architectures while viewing the affective aspect with skepticism. However, scientific studies continue to reveal the deeply intertwined and complementary roles that cognition and emotion play in intelligent decision-making, planning, learning, attention, communication, social interaction, memory, and more. Such findings provide valuable insights and lessons for the design of autonomous robots that must operate in complex and uncertain environments and perform in cooperation with people. This paper presents a concrete implementation of how these insights have guided our work, focusing on the design of sociable autonomous robots that interact with people as capable partners.

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    (2007) · Journal of the Association for Information Systems · Cited by 17

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Metadata

Authors
Breazeal, C.
Venue
IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)
Published
2004-05
Volume
34
Issue
2
Pages
187-194
ISSN
1094-6977 (ISSN-L)
OpenAlex
W2127536482
Cited by
170
References
2
FWCI
13.53
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Function Meets Style: Insights From Emotion Theory Applied to HRI. https://app.cochat.ai/papers/10.1109/tsmcc.2004.826270
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Breazeal, C. (2004). Function Meets Style: Insights From Emotion Theory Applied to HRI. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews). https://doi.org/10.1109/tsmcc.2004.826270

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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.