<div class="csl-bib-body">
<div class="csl-entry">Dobrosovestnova, A., Reinboth, T., & Weiss, A. (2024). Towards an Integrative Framework for Robot Personality Research. <i>ACM Transactions on Computer-Human Interaction</i>, <i>13</i>(1), 1–22. https://doi.org/10.1145/3640010</div>
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dc.identifier.issn
1073-0516
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/196898
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dc.description.abstract
Within human-robot interaction (HRI), research on robot personality has largely drawn on trait theories and models, such as the Big Five and OCEAN. We argue that reliance on trait models in HRI has led to a limited understanding of robot personality as a question of stable traits that can be designed into a robot plus how humans with certain traits respond to particular robots. However, trait-based approaches exist alongside other ways of understanding personality, including approaches focusing on more dynamic constructs such as adaptations and narratives. We suggest that a deep understanding of robot personality is only possible through a cross-disciplinary effort to integrate these different approaches. We propose an Integrative Framework for Robot Personality Research (IF), wherein robot personality is defined not as a property of the robot, nor of the human perceiving the robot, but as a complex assemblage of components at the intersection of robot design and human factors. With the IF, we aim to establish a common theoretical grounding for robot personality research that incorporates personality constructs beyond traits and treats these constructs as complementary and fundamentally interdependent.
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dc.description.sponsorship
Österr. Akademie der Wissenschaften
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dc.language.iso
en
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dc.publisher
ASSOC COMPUTING MACHINERY
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dc.relation.ispartof
ACM Transactions on Computer-Human Interaction
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dc.subject
Human-robot interaction
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dc.subject
personality levels
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dc.subject
robot personality
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dc.title
Towards an Integrative Framework for Robot Personality Research