Difference between revisions of "Rolletetal2017"
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|Author(s)=Nicolas Rollet; Varun Jain; Christian Licoppe; Laurence Devillers; | |Author(s)=Nicolas Rollet; Varun Jain; Christian Licoppe; Laurence Devillers; | ||
|Title=Towards Interactional Symbiosis: Epistemic Balance and Co-presence in a Quantified Self Experiment | |Title=Towards Interactional Symbiosis: Epistemic Balance and Co-presence in a Quantified Self Experiment | ||
| − | |Tag(s)=EMCA; conversation analysis; epistemics; human-robot interaction; preference; quantified self; robots | + | |Tag(s)=EMCA; conversation analysis; epistemics; human-robot interaction; preference; quantified self; robots; AI reference list |
|Key=Rolletetal2017 | |Key=Rolletetal2017 | ||
|Year=2017 | |Year=2017 | ||
Revision as of 00:08, 24 February 2021
| Rolletetal2017 | |
|---|---|
| BibType | INCOLLECTION |
| Key | Rolletetal2017 |
| Author(s) | Nicolas Rollet, Varun Jain, Christian Licoppe, Laurence Devillers |
| Title | Towards Interactional Symbiosis: Epistemic Balance and Co-presence in a Quantified Self Experiment |
| Editor(s) | |
| Tag(s) | EMCA, conversation analysis, epistemics, human-robot interaction, preference, quantified self, robots, AI reference list |
| Publisher | |
| Year | 2017 |
| Language | |
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| Journal | |
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| Number | |
| Pages | 143–154 |
| URL | Link |
| DOI | 10.1007/978-3-319-57753-1_13 |
| ISBN | |
| Organization | |
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| School | |
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| Howpublished | |
| Book title | Lecture Notes in Computer Science |
| Chapter | |
Abstract
In the frame of an experiment dealing with quantified-self and re- flexivity, we collected audio-video data that provide us with material to discuss the ways in which the participants would work out social synergy through co- presence management and epistemic balance – accounting for their orientation towards the familiar symbiotic nature of human interactions. Following a Con- versational Analysis perspective, we believe that detailed analysis of interactio- nal behaviors offers opportunities for socially interactive robots design impro- vements, that is: identify and reproduce human ordinary skills in order to make the machines more adaptable.
Notes
