Difference between revisions of "Lohse-etal2009"

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(Created page with "{{BibEntry |BibType=ARTICLE |Author(s)=Manja Lohse; Marc Hanheide; Karola Pitsch; Katharina J. Rohlfng; Gerhard Sagerer; |Title=Improving HRI design by applying Systemic Int...")
 
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{{BibEntry
 
{{BibEntry
 
|BibType=ARTICLE
 
|BibType=ARTICLE
|Author(s)=Manja Lohse; Marc Hanheide; Karola Pitsch;  Katharina J. Rohlfng; Gerhard Sagerer;
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|Author(s)=Manja Lohse; Marc Hanheide; Karola Pitsch;  Katharina J. Rohlfing; Gerhard Sagerer;
|Title=Improving HRI design by applying Systemic Interaction Analysis (SinA)
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|Title=Improving HRI design by applying Systemic Interaction Analysis (SinA)
 
|Tag(s)=EMCA; analysis tools; user studies; autonomous robots;
 
|Tag(s)=EMCA; analysis tools; user studies; autonomous robots;
 
|Key=Lohse-etal2009
 
|Key=Lohse-etal2009
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|Volume=10
 
|Volume=10
 
|Number=3
 
|Number=3
|Pages=298-323
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|Pages=298–323
|DOI= 10.1075/is.10.3.03loh
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|URL=https://benjamins.com/catalog/is.10.3.03loh
|Abstract=
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|DOI=10.1075/is.10.3.03loh
Social robots are designed to interact with humans. That is why they need  
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|Abstract=Social robots are designed to interact with humans. That is why they need interaction models that take social behaviors into account. These usually influence many of a robot’s abilities simultaneously. Hence, when designing robots that users will want to interact with, all components need to be tested in the system context, with real users and real tasks in real interactions. This requires methods that link the analysis of the robot’s internal computations within and between components (system level) with the interplay between robot and user (interaction level). This article presents Systemic Interaction Analysis (SInA) as an integrated method to (a) derive prototypical courses of interaction based on system and interaction level, (b) identify deviations from these, (c) infer the causes of deviations by analyzing the system’s operational sequences, and (d) improve the robot iteratively by adjusting models and implementations.
interaction models that take social behaviors into account. These usually  
 
influence many of a robot’s abilities simultaneously. Hence, when designing  
 
robots that users will want to interact with, all components need to be tested in  
 
the system context, with real users and real tasks in real interactions. This requires  
 
methods that link the analysis of the robot’s internal computations within and  
 
between components (system level) with the interplay between robot and user  
 
(interaction level). This article presents Systemic Interaction Analysis (SInA)  
 
as an integrated method to (a) derive prototypical courses of interaction based  
 
on system and interaction level, (b) identify deviations from these, (c) infer the  
 
causes of deviations by analyzing the system’s operational sequences, and
 
(d) improve the robot iteratively by adjusting models and implementations.
 
 
 
 
}}
 
}}

Revision as of 10:36, 23 November 2019

Lohse-etal2009
BibType ARTICLE
Key Lohse-etal2009
Author(s) Manja Lohse, Marc Hanheide, Karola Pitsch, Katharina J. Rohlfing, Gerhard Sagerer
Title Improving HRI design by applying Systemic Interaction Analysis (SinA)
Editor(s)
Tag(s) EMCA, analysis tools, user studies, autonomous robots
Publisher
Year 2009
Language
City
Month
Journal Interaction Studies
Volume 10
Number 3
Pages 298–323
URL Link
DOI 10.1075/is.10.3.03loh
ISBN
Organization
Institution
School
Type
Edition
Series
Howpublished
Book title
Chapter

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Abstract

Social robots are designed to interact with humans. That is why they need interaction models that take social behaviors into account. These usually influence many of a robot’s abilities simultaneously. Hence, when designing robots that users will want to interact with, all components need to be tested in the system context, with real users and real tasks in real interactions. This requires methods that link the analysis of the robot’s internal computations within and between components (system level) with the interplay between robot and user (interaction level). This article presents Systemic Interaction Analysis (SInA) as an integrated method to (a) derive prototypical courses of interaction based on system and interaction level, (b) identify deviations from these, (c) infer the causes of deviations by analyzing the system’s operational sequences, and (d) improve the robot iteratively by adjusting models and implementations.

Notes