UN MODELO LÓGICO-FORMAL PARA EL ESTUDIO DE LOS ARGUMENTOS EMOCIONALES EN LOS PROCESOS DE CONSTRUCCIÓN DE ACUERDOS/ A LOGICAL-FORMAL MODEL FOR THE STUDY OF EMOTIONAL ARGUMENTS IN NEGOTIATION PROCESSES/ UM MODELO LÓGICO-FORMAL PARA O ESTUDO DOS ARGUMENTOS EMOCIONAIS NOS PROCESSOS DE CONSTRUÇÃO DE ACORDOS

Los argumentos son parte de un proceso comunicativo con el cual se trata de incidir en la acción de otros. Gilbert (1994) identifica cuatro modos de argumentación: el modo lógico, el modo emocional, el modo visceral y el modo kisceral. Siguiendo la línea de investigación en psicología computacional marcada por Ortony, Clore y Collins (1988) y el modelo de resolución de conflictos usando negociaciones basadas en argumentos propuesto por Jung y Tambe (2001), este trabajo presenta un modelo lógico-formal para el estudio de un modo concreto de argumentos emocionales dentro del contexto de formación de consensos enmarcado en un proceso de negociación/coordinación. Se discuten sus implicaciones en los modelos cognitivos emocionales basados en el proceso de apreciación/evaluación de la emoción

Detection of Sarcasm and Nastiness: New Resources for Spanish Language

The main goal of this work is to provide the cognitive computing community with valuable resources to analyze and simulate the intentionality and/or emotions embedded in the language employed in social media. Specifically, it is focused on the Spanish language and online dialogues, leading to the creation of SOFOCO (Spanish Online Forums Corpus). It is the first Spanish corpus consisting of dialogic debates extracted from social media and it is annotated by means of crowdsourcing in order to carry out automatic analysis of subjective language forms, like sarcasm or nastiness. Furthermore, the annotators were also asked about the context need when taking a decision. In this way, the users’ intentions and their behavior inside social networks can be better understood and more accurate text analysis is possible. An analysis of the annotation results is carried out and the reliability of the annotations is also explored. Additionally, sarcasm and nastiness detection results (around 0.76 F-Measure in both cases) are also reported. The obtained results show the presented corpus as a valuable resource that might be used in very diverse future work.This study was partially funded by the Spanish Government (TIN2014-54288-C4-4-R and TIN2017-85854-C4-3-R) by the European Unions’s H2020 program under grant 769872 and by the National Science Foundation of USA (NSF CISE R1 #1202668

Emotion-involved human decision-making model

This study proposes a computational human decision-making model that handles emotion-induced behaviour. The proposed model can determine a rational or irrational action according to a probability distribution obtained by mixing an optimal policy of a partially observable Markov decision process and an evolved probability distribution by novel dynamics of emotions. Emotion dynamics with consecutive negative observations cause emotion-induced irrational behaviours. We clarify the conditions, via two theorems, that the proposed model computes rational and irrational actions in terms of some model parameters. A numerical example based on Japanese court records is used to confirm that the proposed model imitates the human decision-making process. Moreover, we discuss the possibility of preventive measures for avoiding the murder case scenario. This study shows that if the traits of a decision maker can be modelled, the proposed model can support human interactions to avoid an emotion-driven murder case scenario

From Affect Theoretical Foundations to Computational Models of Intelligent Affective Agents

[EN] The links between emotions and rationality have been extensively studied and discussed. Several computational approaches have also been proposed to model these links. However, is it possible to build generic computational approaches and languages so that they can be "adapted " when a specific affective phenomenon is being modeled? Would these approaches be sufficiently and properly grounded? In this work, we want to provide the means for the development of these generic approaches and languages by making a horizontal analysis inspired by philosophical and psychological theories of the main affective phenomena that are traditionally studied. Unfortunately, not all the affective theories can be adapted to be used in computational models; therefore, it is necessary to perform an analysis of the most suitable theories. In this analysis, we identify and classify the main processes and concepts which can be used in a generic affective computational model, and we propose a theoretical framework that includes all these processes and concepts that a model of an affective agent with practical reasoning could use. Our generic theoretical framework supports incremental research whereby future proposals can improve previous ones. This framework also supports the evaluation of the coverage of current computational approaches according to the processes that are modeled and according to the integration of practical reasoning and affect-related issues. This framework is being used in the development of the GenIA(3) architecture.This work is partially supported by the Spanish Government projects PID2020-113416RB-I00, GVA-CEICE project PROMETEO/2018/002, and TAILOR, a project funded by EU Horizon 2020 research and innovation programme under GA No 952215.Alfonso, B.; Taverner-Aparicio, JJ.; Vivancos, E.; Botti, V. (2021). From Affect Theoretical Foundations to Computational Models of Intelligent Affective Agents. Applied Sciences. 11(22):1-29. https://doi.org/10.3390/app112210874S129112

EEG-Based Empathic Safe Cobot

An empathic collaborative robot (cobot) was realized through the transmission of fear from a human agent to a robot agent. Such empathy was induced through an electroencephalographic (EEG) sensor worn by the human agent, thus realizing an empathic safe brain-computer interface (BCI). The empathic safe cobot reacts to the fear and in turn transmits it to the human agent, forming a social circle of empathy and safety. A first randomized, controlled experiment involved two groups of 50 healthy subjects (100 total subjects) to measure the EEG signal in the presence or absence of a frightening event. The second randomized, controlled experiment on two groups of 50 different healthy subjects (100 total subjects) exposed the subjects to comfortable and uncomfortable movements of a collaborative robot (cobot) while the subjects’ EEG signal was acquired. The result was that a spike in the subject’s EEG signal was observed in the presence of uncomfortable movement. The questionnaires were distributed to the subjects, and confirmed the results of the EEG signal measurement. In a controlled laboratory setting, all experiments were found to be statistically significant. In the first experiment, the peak EEG signal measured just after the activating event was greater than the resting EEG signal (p < 10−3). In the second experiment, the peak EEG signal measured just after the uncomfortable movement of the cobot was greater than the EEG signal measured under conditions of comfortable movement of the cobot (p < 10−3). In conclusion, within the isolated and constrained experimental environment, the results were satisfactory

Developing an emotional-based application for human-agent societies

The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-016-2289-5The purpose of this paper is to present an emotional-based application for human-agent societies. This kind of applications are those where virtual agents and humans coexist and interact transparently into a fully integrated environment. Specifically, the paper presents an application where humans are immersed into a system that extracts and analyzes the emotional states of a human group trying to maximize the welfare of those humans by playing the most appropriate music in every moment. This system can be used not only online, calculating the emotional reaction of people in a bar to a new song, but also in simulation, to predict the people s reaction to changes in music or in the bar layout.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.Rincón Arango, JA.; Julian Inglada, VJ.; Carrascosa Casamayor, C. 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Human emotion simulation in a dynamic environment

The aim of this work is to contribute to the believability of the simulated emotions for virtual entities to allow them display human like features. Endowing virtual entities with such features requires an appropriate architecture and model. For that, a study of emotional models from different perspective is undertaken. The fields include Psychology, Organic Components, Attention study and Computing. Two contributions are provided to reach the aim. The first one is a computational emotional model based on Scherer’s theory (K. Scherer, 2001). This contribution allows to generate a series of modifications in the affective state from one event by contrast to the existing solutions where one emotion is mapped to one single event. Several theories are used to make the model concrete. The second contribution make use of attention theories to build a paradigm in the execution of tasks in parallel. An algorithm is proposed to assess the available resources and allocate them to tasks for their execution. The algorithm is based on the multiple resources theory by Wickens (Wickens, 2008). The two contributions are combined into one architecture to produce a dynamic emotional system that allows its components to work in parallel. The first contribution was evaluated using a questionnaire. The results showed that mapping one event into a series of modifications in the affective state can enhance the believability of the simulation. The results also showed that people who develop more variations in the affective state are more perceived to be feminine