Influencing over people with a social emotional model

[EN] This paper presents an approach of a social emotional model, which allows to extract the social emotion of a group of intelligent entities. The emotional model PAD allows to represent the emotion of an intelligent entity in 3-D space, allowing the representation of different emotional states. The social emotional model presented in this paper uses individual emotions of each one of the entities, which are represented in the emotional space PAD. Using a social emotional model within intelligent entities allows the creation of more real simulations, in which emotional states can influence decision-making. The result of this social emotional mode is represented by a series of examples, which are intended to represent a number of situations in which the emotions of each individual modify the emotion of the group. Moreover, the paper introduces an example which employs the proposed model in order to learn and predict future actions trying to influence in the social emotion of a group of people.This work is partially supported by the MINECO/FEDER TIN2015-65515-C4-1-R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon.Rincon, J.; De La Prieta-Pintado, F.; Zanardini, D.; Julian Inglada, VJ.; Carrascosa Casamayor, C. (2017). Influencing over people with a social emotional model. Neurocomputing. 231:47-54. https://doi.org/10.1016/j.neucom.2016.03.107S475423

Social emotional model for coping with learning among adolescent secondary school students

Social emotions are frequently experienced in every individual in the daily life including adolescents’ secondary school students. The mult-social emotional changes such as aggressive and happiness among adolescents influences students coping with learning at school. The purpose of this study was to develop social emotional model for coping with learning among adolescent secondary school students. Specifically the study attempted to answer the extent social emotional model is effective in improving students coping with learning. The study adapted collaborative action research design in which a total of 244 adolescent secondary school students responded to questionnaires and focus group discussion. The effectiveness of the developed social emotional model for student coping with learning was reported by students through the questionnaires. It was found that the aspects incorporated in the model improved practices in learning outcomes to both teachers and students in coping with learning. It was found that, Teachers used guidance and counseling, action oriented activities such as role play, encouraging play and exploration as the strategies to foster active engagement among adolescent secondary school students towards learning adjustment. Furthermore, the study revealed positive significant because the data in the model summary shows that the value of r=.351 indicates that one item for adolescent secondary school students coping with learning increased for about 35.1% with 77.5% standard error of the estimated predictor value. Although this study was conducted in Tanzania employing moderate sample size from which the data was gathered with the help of collaboration action research design. The findings provide guidelines for further replicate research on social emotion behaviours and academic performance in education elsewhere

Performance pay, group selection and group performance

Within a laboratory experiment we investigate a principal-agent game in which agents may, first, self-select into a group task (GT) or an individual task (IT) and, second, choose work effort. In their choices of task and effort the agents have to consider pay contracts for both tasks as offered by the principal. The rational solution of the game implies that contract design may not induce agents to select GT and provide positive effort in GT. Furthermore it predicts equal behavior of agents with different productivities. In contrast, considerations of trust, reciprocity and cooperation – the social-emotional model of behavior – suggest that contract design can influence the agents’ willingness to join groups and provide effort. We analyze the data by applying a two-step regression model (multinomial logit and tobit) and find that counter to the rational solution, contract design does influence both, task selection and effort choice. The principal can increase participation in work groups and can positively influence group performance. Larger payment increases the share of socially motivated agents in work groups. The selection effect is larger than the motivation effect

Adding real data to detect emotions by means of smart resource artifacts in MAS

[EN] This article proposes an application of a social emotional model, which allows to extract, analyse, represent and manage the social emotion of a group of entities. Specifically, the application is based on how music can influence in a positive or negative way over emotional states. The proposed approach employs the JaCalIVE framework, which facilitates the development of this kind of environments. A physical device called smart resource offers to agents processed sensor data as a service. So that, agents obtain real data from a smart resource. MAS uses the smart resource as an artifact by means of a specific communications protocol. The framework includes a design method and a physical simulator. In this way, the social emotional model allows the creation of simulations over JaCalIVE, in which the emotional states are used in the decision-making of the agents.This work is partially supported by the MINECO/FEDER TIN2015-65515-C4-1-R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon.Ricon, JA.; Poza-Lujan, J.; Posadas-Yagüe, J.; Julian Inglada, VJ.; Carrascosa Casamayor, C. (2016). Adding real data to detect emotions by means of smart resource artifacts in MAS. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal. 5(4):85-92. https://doi.org/10.14201/ADCAIJ2016548592S85925

Social Emotions in Multiagent Systems

Tesis por compendioA lo largo de los últimos años, los sistemas multi-agente (SMA) han demostrado ser un paradigma potente y versátil, con un gran potencial a la hora de resolver problemas complejos en entornos dinámicos y distribuidos. Este potencial no se debe principalmente a sus características individuales (como son su autonomía, su capacidad de percepción, reacción y de razonamiento), sino que también a la capacidad de comunicación y cooperación a la hora de conseguir un objetivo. De hecho, su capacidad social es la que más llama la atención, es este comportamiento social el que dota de potencial a los sistemas multi-agente. Estas características han hecho de los SMA, la herramienta de inteligencia artificial (IA) más utilizada para el diseño de entornos virtuales inteligentes (IVE), los cuales son herramientas de simulación compleja basadas en agentes. Sin embargo, los IVE incorporan restricciones físicas (como gravedad, fuerzas, rozamientos, etc.), así como una representación 3D de lo que se quiere simular. Así mismo, estas herramientas no son sólo utilizadas para la realización de simulaciones. Con la aparición de nuevas aplicaciones como \emph{Internet of Things (IoT)}, \emph{Ambient Intelligence (AmI)}, robot asistentes, entre otras, las cuales están en contacto directo con el ser humano. Este contacto plantea nuevos retos a la hora de interactuar con estas aplicaciones. Una nueva forma de interacción que ha despertado un especial interés, es el que se relaciona con la detección y/o simulación de estados emocionales. Esto ha permitido que estas aplicaciones no sólo puedan detectar nuestros estados emocionales, sino que puedan simular y expresar sus propias emociones mejorando así la experiencia del usuario con dichas aplicaciones. Con el fin de mejorar la experiencia humano-máquina, esta tesis plantea como objetivo principal la creación de modelos emocionales sociales, los cuales podrán ser utilizados en aplicaciones MAS permitiendo a los agentes interpretar y/o emular diferentes estados emocionales y, además, emular fenómenos de contagio emocional. Estos modelos permitirán realizar simulaciones complejas basadas en emociones y aplicaciones más realistas en dominios como IoT, AIm, SH.Over the past few years, multi-agent systems (SMA) have proven to be a powerful and versatile paradigm, with great potential for solving complex problems in dynamic and distributed environments. This potential is not primarily due to their individual characteristics (such as their autonomy, their capacity for perception, reaction and reasoning), but also the ability to communicate and cooperate in achieving a goal. In fact, its social capacity is the one that draws the most attention, it is this social behavior that gives potential to multi-agent systems. These characteristics have made the SMA, the artificial intelligence (AI) tool most used for the design of intelligent virtual environments (IVE), which are complex agent-based simulation tools. However, IVE incorporates physical constraints (such as gravity, forces, friction, etc.), as well as a 3D representation of what you want to simulate. Also, these tools are not only used for simulations. With the emergence of new applications such as \emph {Internet of Things (IoT)}, \emph {Ambient Intelligence (AmI)}, robot assistants, among others, which are in direct contact with humans. This contact poses new challenges when it comes to interacting with these applications. A new form of interaction that has aroused a special interest is that which is related to the detection and / or simulation of emotional states. This has allowed these applications not only to detect our emotional states, but also to simulate and express their own emotions, thus improving the user experience with those applications. In order to improve the human-machine experience, this thesis aims to create social emotional models, which can be used in MAS applications, allowing agents to interpret and / or emulate different emotional states, and emulate phenomena of emotional contagion. These models will allow complex simulations based on emotions and more realistic applications in domains like IoT, AIm, SH.Al llarg dels últims anys, els sistemes multi-agent (SMA) han demostrat ser un paradigma potent i versàtil, amb un gran potencial a l'hora de resoldre problemes complexos en entorns dinàmics i distribuïts. Aquest potencial no es deu principalment a les seues característiques individuals (com són la seua autonomia, la seua capacitat de percepció, reacció i de raonament), sinó que també a la capacitat de comunicació i cooperació a l'hora d'aconseguir un objectiu. De fet, la seua capacitat social és la que més crida l'atenció, és aquest comportament social el que dota de potencial als sistemes multi-agent. Aquestes característiques han fet dels SMA, l'eina d'intel·ligència artificial (IA) més utilitzada per al disseny d'entorns virtuals intel·ligents (IVE), els quals són eines de simulació complexa basades en agents. No obstant això, els IVE incorporen restriccions físiques (com gravetat, forces, fregaments, etc.), així com una representació 3D del que es vol simular. Així mateix, aquestes eines no són només utilitzades per a la realització de simulacions. Amb l'aparició de noves aplicacions com \emph{Internet of Things (IOT)}, \emph{Ambient Intelligence (AmI)}, robot assistents, entre altres, les quals estan en contacte directe amb l'ésser humà. Aquest contacte planteja nous reptes a l'hora d'interactuar amb aquestes aplicacions. Una nova forma d'interacció que ha despertat un especial interès, és el que es relaciona amb la detecció i/o simulació d'estats emocionals. Això ha permès que aquestes aplicacions no només puguen detectar els nostres estats emocionals, sinó que puguen simular i expressar les seues pròpies emocions millorant així l'experiència de l'usuari amb aquestes aplicacions. Per tal de millorar l'experiència humà-màquina, aquesta tesi planteja com a objectiu principal la creació de models emocionals socials, els quals podran ser utilitzats en aplicacions MAS permetent als agents interpretar i/o emular diferents estats emocionals i, a més, emular fenòmens de contagi emocional. Aquests models permetran realitzar simulacions complexes basades en emocions i aplicacions més realistes en dominis com IoT, AIM, SH.Rincón Arango, JA. (2018). Social Emotions in Multiagent Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/98090TESISCompendi

Detecting social emotions with a NAO robot

This article aims to give an approach of a dynamic and emotional propagation, which allows to calculate the propagation of the emotion of a group of humans and/or intelligent entities. The dynamic model is based on the Newton laws in order to calculate the emotional attraction among them. To obtain the emotions we use a NAO robot as a tool to move around of a real environment for interacting with the humans. The robot obtains the emotions through image processing. Moreover, the robot can start a dialogue game with humans in order to estimate the personality of a new individual.This work is partially supported by the MINECO project TIN2015-65515-C4-1- R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon

A dynamic emotional model for agent societies

This paper presents a first approximation of a dynamic emotional model to be employed in agent societies. The proposed model is based on the PAD emotional model and allows the representation of the emotional contagion phenomena of a heterogeneous group of agents which are capable of express emotions. Moreover, the proposal allows the definition of the social emotion of this group of agents. The model is mainly based on three elements: personality, empathy and affinity. These elements allow the characterization of each individual, causing them susceptible to vary in some degre the emotions of other individuals

Social Emotional Model for Coping with Learning among Adolescent Secondary School Students in Tanzania: A Case Study of Hai District.

The purpose of this study was to develop social emotional learning model for coping with learning among adolescent secondary school students. The study adapted collaborative action and quasi- experimental research design in which a total of 244 adolescent secondary school students responded to questionnaires and participated in focus group discussions. Students’ emotions and social emotions strategies were reported by teachers through the interview and researchers observations during recess time. It was found that, about 83% of adolescent students’ demonstrated variety social emotions at school, including fighting in the class, kicking, joyful and excitement. However, aggressive social emotions had negative correlation between students coping with learning at secondary school, while positive emotions revealed positive significant correlation between students coping with learning at secondary schools. Positive significant correlation was revealed between guidance and counseling (β=.298, t(4, 239)= 4.93, p=.000) and student coping with learning. The model revealed r=0.351(35.1%) which significantly improved adolescent social emotional skills. The study recommends that policy makers should provide programmes and a framework for effective management of social emotions behaviours among adolescent students at schools. This study employed moderate sample size. Broader base schools could be used for analysis in order to determine the applicability of social emotional learning model over time. Keywords: Social Emotions, Coping, Attachment, Emotional competencies

To connect is to be influenced: What determines a third-party's forgiveness attitudes to conflicting groups' violent partisan members?

The present research seeks to answer the question of what determines an uninvolved third party's forgiveness attitudes toward conflicting groups' violent partisan members. Specifically, Bangladeshi participants read a fictitious interview with a radicalized Palestinian who declared his intention to avenge himself against Israelis for his personal and collective plight by carrying out a suicide bombing attack. Findings reveal that an empathy manipulation (high empathy = other focused or low empathy = objective focused) influenced participants' forgiveness attitudes towards the radicalized Palestinian such that in the high empathy condition participants were more forgiving of the target than participants in the low empathy condition. Moreover, while the strength of their religious identification (Islam) played no significant role, participants' tendency to attribute the target's decision to situational factors fully mediated the effects of empathy on forgiveness

Activities suggestion based on emotions in AAL environments

The elderly population is increasing and the response of the society was to provide them with services directed to them to cope with their needs. One of the oldest solutions is the retirement home, providing housing and permanent assistance for the elderly. Furthermore, most of the retirement homes are inhabited by multiple elderly people, thus creating a community of people who are somewhat related in age and medical issues. The ambient assisted living (AAL) area tries to solve some of the elderly issues by producing technological products, some of them dedicated to elderly homes. One of the identified problem is that elderly people are sometimes discontent about the activities that consume most of their day promoted by the retirement home social workers. The work presented in this paper attempts to improve how these activities are scheduled taking into account the elderlies' emotional response to these activities. The aim is to maximize the group happiness by promoting the activities the group likes, minding if they are bored due to activities repetition. In this sense, this paper presents an extension of the Cognitive Life Assistant platform incorporating a social emotional model. The proposed system has been modelled as a free time activity manager which is in charge of suggesting activities to the social workers. (C) 2018 Elsevier B.V. All rights reserved.Angelo Costa thanks the Fundacao para a Ciencia e a Tecnologia (FCT) the Post-Doc scholarship with the Ref. SFRH/BPD/102696/2014. This work is also supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013 and partially supported by the MINECO/FEDER TIN2015-65515-C4-1-R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon