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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Detalles Bibliográficos
Autores: Andriella, Antonio|||0000-0002-6641-6450, Siqueira, Henrique, Fu, Di, Magg, Sven, Barros, Pablo, Wermter, Stefan, Torras, Carme|||0000-0002-2933-398X, Alenyà Ribas, Guillem|||0000-0002-6018-154X
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/336278
Acceso en línea:https://hdl.handle.net/2117/336278
https://dx.doi.org/10.1007/s12369-020-00690-5
Access Level:acceso abierto
Palabra clave:Robotics
Artificial intelligence
Robòtica
Intel·ligència artificial
Àrees temàtiques de la UPC::Informàtica::Robòtica
Descripción
Sumario: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.