Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits

Recent studies have revealed the key importance of modelling personality in robots to improve interaction quality by empowering them with social-intelligence capabilities. Most research relies on verbal and non-verbal features related to personality traits that are highly context-dependent. Hence, a...

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Autores: Andriella, Antonio, Siqueira, Henrique, Fu, Di, Magg, Sven, Barros, Pablo, Wermter, Stefen, Torras, Carme, Alenyà, Guillem
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/261297
Acceso en línea:http://hdl.handle.net/10261/261297
Access Level:acceso abierto
Palabra clave:Robot personalities
Human–human interaction
Human–robot interaction
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spelling Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality TraitsAndriella, AntonioSiqueira, HenriqueFu, DiMagg, SvenBarros, PabloWermter, StefenTorras, CarmeAlenyà, GuillemRobot personalitiesHuman–human interactionHuman–robot interactionRecent studies have revealed the key importance of modelling personality in robots to improve interaction quality by empowering them with social-intelligence capabilities. Most research relies on verbal and non-verbal features related to personality traits that are highly context-dependent. Hence, analysing how humans behave in a given context is crucial to evaluate which of those social cues are effective. For this purpose, we designed an assistive memory game, in which participants were asked to play the game obtaining support from an introvert or extroverted helper, whether from a human or robot. In this context, we aim to (i) explore whether selective verbal and non-verbal social cues related to personality can be modelled in a robot, (ii) evaluate the efficiency of a statistical decision-making algorithm employed by the robot to provide adaptive assistance, and (iii) assess the validity of the similarity attraction principle. Specifically, we conducted two user studies. In the human–human study (N=31), we explored the effects of helper’s personality on participants’ performance and extracted distinctive verbal and non-verbal social cues from the human helper. In the human–robot study (N=24), we modelled the extracted social cues in the robot and evaluated its effectiveness on participants’ performance. Our findings showed that participants were able to distinguish between robots’ personalities, and not between the level of autonomy of the robot (Wizard-of-Oz vs fully autonomous). Finally, we found that participants achieved better performance with a robot helper that had a similar personality to them, or a human helper that had a different personality.This work is supported by the German Research Foundation (DFG), National Natural Science Foundation of China (NSFC), under project Transregio Crossmodal Learning (DFG TRR 169/NSFC 61621136008), and a CAS-DAAD joint fellowship. This project has also been partially funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skł, odowska-Curie grant agreement SOCRATES (no. 721619), by the European Union’s Horizon 2020 under grant agreement CLOTHILDE (no. 741930), by the Spanish Ministry of Science and Innovation HuMoUR (TIN2017-90086-R), and by the Spanish State Research Agency through the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656).Springer NatureGerman Research FoundationNational Natural Science Foundation of ChinaEuropean CommissionMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)Ministerio de Economía y Competitividad (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2022202220212022info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/261297reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/721619info:eu-repo/grantAgreement/EC/H2020/741930info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-90086-Rinfo:eu-repo/grantAgreement/MINECO//MDM-2016-0656http://dx.doi.org/10.1007/s12369-020-00690-5Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2612972026-05-22T06:33:51Z
dc.title.none.fl_str_mv Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
title Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
spellingShingle Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
Andriella, Antonio
Robot personalities
Human–human interaction
Human–robot interaction
title_short Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
title_full Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
title_fullStr Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
title_full_unstemmed Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
title_sort Do I Have a Personality? Endowing Care Robots with Context-Dependent Personality Traits
dc.creator.none.fl_str_mv Andriella, Antonio
Siqueira, Henrique
Fu, Di
Magg, Sven
Barros, Pablo
Wermter, Stefen
Torras, Carme
Alenyà, Guillem
author Andriella, Antonio
author_facet Andriella, Antonio
Siqueira, Henrique
Fu, Di
Magg, Sven
Barros, Pablo
Wermter, Stefen
Torras, Carme
Alenyà, Guillem
author_role author
author2 Siqueira, Henrique
Fu, Di
Magg, Sven
Barros, Pablo
Wermter, Stefen
Torras, Carme
Alenyà, Guillem
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv German Research Foundation
National Natural Science Foundation of China
European Commission
Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
Ministerio de Economía y Competitividad (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Robot personalities
Human–human interaction
Human–robot interaction
topic Robot personalities
Human–human interaction
Human–robot interaction
description Recent studies have revealed the key importance of modelling personality in robots to improve interaction quality by empowering them with social-intelligence capabilities. Most research relies on verbal and non-verbal features related to personality traits that are highly context-dependent. Hence, analysing how humans behave in a given context is crucial to evaluate which of those social cues are effective. For this purpose, we designed an assistive memory game, in which participants were asked to play the game obtaining support from an introvert or extroverted helper, whether from a human or robot. In this context, we aim to (i) explore whether selective verbal and non-verbal social cues related to personality can be modelled in a robot, (ii) evaluate the efficiency of a statistical decision-making algorithm employed by the robot to provide adaptive assistance, and (iii) assess the validity of the similarity attraction principle. Specifically, we conducted two user studies. In the human–human study (N=31), we explored the effects of helper’s personality on participants’ performance and extracted distinctive verbal and non-verbal social cues from the human helper. In the human–robot study (N=24), we modelled the extracted social cues in the robot and evaluated its effectiveness on participants’ performance. Our findings showed that participants were able to distinguish between robots’ personalities, and not between the level of autonomy of the robot (Wizard-of-Oz vs fully autonomous). Finally, we found that participants achieved better performance with a robot helper that had a similar personality to them, or a human helper that had a different personality.
publishDate 2021
dc.date.none.fl_str_mv 2021
2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/261297
url http://hdl.handle.net/10261/261297
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
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#PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/H2020/721619
info:eu-repo/grantAgreement/EC/H2020/741930
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-90086-R
info:eu-repo/grantAgreement/MINECO//MDM-2016-0656
http://dx.doi.org/10.1007/s12369-020-00690-5
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
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