Modeling of emotion elicitation conditions for a cognitive-emotive architecture

Jain, Shikha; Asawa, Krishna

doi:10.1016/j.cogsys.2018.12.012

Cited by 12 publications

(8 citation statements)

References 26 publications

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“…In examining H5, the results showed that the participants’ emotional engagement was negatively related to their turnover intention. Additionally, Jain and Asawa (2019) suggested that engagement plays an important role in generating behavioral responses. In examining H6, the results showed that participants’ remote behavioral engagement was negatively related to their turnover intention, indicating that employees who have more behavioral engagement will show less turnover intention.…”

Section: Discussionmentioning

confidence: 99%

“…Ecological theories focus on the interaction of persons and environments requiring individual unique physical and psychological adaptations ( Bronfenbrenner, 1995 ). This suggests that engagement plays an important role in generating behavioral responses ( Jain and Asawa, 2019 ; McLaughlin et al, 2019 ); thus, during the COVID-19 lockdown, the research model for investigating the relationship between positive affect, remote WE, and turnover intention of R&D professionals was proposed as shown in Figure 1 .…”

Section: Hypothesesmentioning

confidence: 99%

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Positive Affect Predicts Turnover Intention Mediated by Online Work Engagement: A Perspective of R&D Professionals in the Information and Communication Technology Industry

2021

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Remote work has become the most popular approach during the COVID-19 lockdown; however, remote work engagement is an issue which creates challenges for human resource management. Some individuals engage in work no matter how difficult the job is, but some people’s minds wander, no matter how simple the job is. To address this issue, this study drew on trait activation theory, which indicates that one’s positive disposition may affect one’s turnover intention mediated by work engagement, to formulate a research model to test the associations among R&D professionals. Questionnaires were distributed to R&D professionals working in China information and communication technology (ICT) through several Instant Message groups. In total, 386 valid questionnaires were collected for confirmatory factor analysis with structural equation modeling to verify the research model. The study found that positive affect can positively predict three types of remote work engagement: the cognitive, emotional, and behavioral engagement of R&D personnel. All three types of remote work engagement of R&D personnel can negatively predict their turnover intention. The results suggest that if human resource managers working in the ICT industry want to reduce the turnover intention rate of R&D workers under pressure from COVID-19, they should enhance workers’ remote engagement by selecting R&D workers with a high level of positive affect.

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Section: Discussionmentioning

confidence: 99%

Section: Hypothesesmentioning

confidence: 99%

Positive Affect Predicts Turnover Intention Mediated by Online Work Engagement: A Perspective of R&D Professionals in the Information and Communication Technology Industry

2021

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“…In recent years, there have been many emotional computing models and cognition-emotion models based on appraisal theory. The emotion elicitation conditions (EECs) model [32] used fuzzy logic to predict the emotional state based upon event appraisal. Rodríguez et al [33] proposed a software systems, based on the purpose of extensive interaction, to generate the emotionally driven responses considering about cognitive component.…”

Section: Related Workmentioning

confidence: 99%

Reinforcement Emotion-Cognition System: A Teaching Words Task

Xie

Zhang

et al. 2019

Computational Intelligence and Neuroscience

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The goal of this paper is to suggest a system for intelligent learning environments with robots modeling of emotion regulation and cognition based on quantitative motivation. A detailed interactive situation for teaching words is proposed. In this study, we introduce one bottom-up collaboration method for emotion-cognition interplay and behaviour decision-making. Integration with gross emotion regulation theory lets the proposed system adapt to natural interactions between students and the robot in emotional interaction. Four key ideas are advocated, and they jointly set up a reinforcement emotion-cognition system (RECS). First, the quantitative motivation is grounded on external interactive sensory detection, which is affected by memory and preference. Second, the emotion generation triggered by an initial motivation such as external stimulus is also influenced by the state in the previous time. Third, the competitive and cooperative relationship between emotion and motivation intervenes to make the decision of emotional expression and teaching actions. Finally, cognitive reappraisal, the emotion regulation strategy, is introduced for the establishment of emotion transition combined with personalized cognition. We display that this RECS increases the robot emotional interactive performance and makes corresponding teaching decision through behavioural and statistical analysis.

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“…En este último elemento teórico referencial se establece la relación de las emociones en el contexto de la cognición desde sus aspectos neurológicos, fisiológicos y psicológicos (Damasio, 1999;Gross, 2012;Halty et al, 2011;Jain & Asawa, 2019). También se consideró el de la inteligencia artificial, particularmente desde la computación afectiva (3.6.1) en donde se clasifican como emociones categóricas, componenciales y dimensionales (Ekman, 1992;Ekman & Oster, 1981;Lisetti & Hudlicka, 2015;Moerland et al, 2018;Mora-Torres, 2015;Mora-Torres et al, 2011;Scherer, 2018) relacionadas a la conducta y a las reacciones observables.…”

Section: Módulo De Interacción Nivelunclassified

“…Como base de aplicación, que se deja como un trabajo futuro, desde el enfoque de las emociones componenciales, se queda el modelo cognitivo OCC de Ortony, Clore y Collins (Jain & Asawa, 2019;Laureano-Cruces et al, 2018;Lisetti & Hudlicka, 2015;Mora-Torres, 2015;Ortony et al, 1996;Ramírez-Laureano et al, 2018) que podría ser aplicado a la interacción. La ubicación de los estados de consciencia de Laurey consideraron una aproximación del nivel de alerta, sin embargo, el equipo del Instituto de Stanford para neuroinnovación y neurociencia (2020) los reubicó con ligeras modificaciones a partir de los correlatos neurológicos detectados por medio del registro encefalográfico.…”

Section: Módulo De Interacción Nivelunclassified

Comportamiento de niños con Trastorno del Espectro Autista (TEA) en el uso de sus funciones ejecutivas suscitadas a partir de interacciones cognitivas con un robot humanoide

Villavicencio¹,

Luz²

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Los niños con Trastorno del Espectro Autista (TEA) presentan primordialmente tres tipos de problemas: 1) patrones de comportamiento como actividades e intereses repetitivos y restringidos; 2) deterioro de la comunicación e interacción social, y 3) deterioro en la flexibilidad de pensamiento (DSM-5). La exploración diagnóstica ha estado mediada por aspectos empíricos, teóricos, metodológicos o epistemológicos. Analizados desde distintas áreas del conocimiento, a través de las cuales se han propuesto diversos tipos de intervenciones. Las explicaciones teóricas más importantes del comportamiento dentro del TEA han enfatizado la falta de interacción social de los niños con otras personas debido a: 1) un deficiente sistema de interpretación de las intenciones y del estado mental de otras personas; 2) la carencia de la optimización de sus funciones ejecutivas (FE) relacionadas con la capacidad para mantener una disposición adecuada durante la solución de problemas a largo plazo, y 3) deficiente adaptación social en relación con la falta de empatía, debido a una alta recurrencia de patrones detectados como las actividades e intereses restringidos y repetitivos. El objetivo que se cumple en la investigación es: describir, visualizar y analizar el comportamiento de niños con TEA mientras interactúan con un robot humanoide empleado como vehículo de interacción asistida para generar un modelo de interacción cognitiva. También ha sido importante evaluar su flexibilidad adaptativa a partir del empleo de sus FE asociadas a un nivel de consciencia. Se consideró la inclusión del robot humanoide debido a la alta aceptación que ha tenido entre los niños, incluyendo a los del espectro autista. A través del robot se desarrollaron tareas para ejercitar algunas de sus FE asociadas a los niveles de consciencia. Se empleó una metodología propia transdisciplinaria con el fin de: 1) explorar, 2) visualizar, y 3) analizar la conducta de los niños bajo condiciones experimentales, con el fin de establecer un modelo de interacción cognitivo. El modelo como resultado de la tesis se pone a prueba con niños con TEA y se sustenta en la alta capacidad de logro de las tareas e intereses que alcanzan los infantes durante las interacciones.

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Modeling of emotion elicitation conditions for a cognitive-emotive architecture

Cited by 12 publications

References 26 publications

Positive Affect Predicts Turnover Intention Mediated by Online Work Engagement: A Perspective of R&D Professionals in the Information and Communication Technology Industry

Positive Affect Predicts Turnover Intention Mediated by Online Work Engagement: A Perspective of R&D Professionals in the Information and Communication Technology Industry

Reinforcement Emotion-Cognition System: A Teaching Words Task

Comportamiento de niños con Trastorno del Espectro Autista (TEA) en el uso de sus funciones ejecutivas suscitadas a partir de interacciones cognitivas con un robot humanoide

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