In this paper, we discuss scripting tools that aim at facilitating the design of web-based interactions with animated characters capable of affective communication. Specifically, two systems are developed. The SCREAM system is a scripting tool that enables authors to create emotionally and socially appropriate responses of animated characters.

This paper introduces a computational model for emotion regulation formalising the model informally described by Gross (1998). The model has been constructed using a highlevel modelling language, and integrates both quantitative aspects (such as levels of emotional response) and qualitative aspects (such as decisions to regulate one’s emotion). A number of simulation experiments have been performed, demonstrating that the computational model successfully reflects the model as described by Gross.

These studies investigated self-regulation and subjective experience of time from the perspective of the regulatory resource model. Studies 1–2 showed that participants who were instructed to regulate their emotions while viewing a film clip perceived that the film lasted longer than participants who did not regulate their emotions. In Study 3, participants provided time estimates during a resource-depleting or nondepleting task. Subsequent task persistence was measured. Time perceptions mediated the effect of initial self-regulation on subsequent self-regulated performance. In Study 4, participants performed either a resource-depleting or a nondepleting thought-listing task and then performed a different regulatory task. Compared with nondepleted participants, depleted participants persisted less on the 2nd task but estimated that they had persisted longer. Subjective time estimates statistically accounted for reduced persistence after depletion. Together, results indicate people believe that self-regulatory endeavors last overly long, a belief that may result in abandonment of further self-control. Put your hand on a hot stove for a minute, and it seems like an hour. Sit with a pretty girl for an hour, and it seems like a minute. THAT’S relativity. —Albert Einstein

This article develops the hypothesis that intervention strategies that cultivate positive emotions are particularly suited for preventing and treating problems rooted in negative emotions, such as anxiety, depression, aggression, and stressrelated health problems. Fredrickson's (1998) broaden–and–build model of positive emotions provides the foundation for this application. According to this model, the form and function of positive and negative emotions are distinct and complementary. Negative emotions (e.g., fear, anger, and sadness) narrow an individual's momentary thought–action repertoire toward specific actions that served the ancestral function of promoting survival. By contrast, positive emotions (e.g., joy, interest, and contentment) broaden an individual's momentary thought–action repertoire, which in turn can build that individual's enduring personal resources, resources that also served the ancestral function of promoting survival. One implication of the broaden–and–build model is that positive emotions have an undoing effect on negative emotions. By broadening

Abstract. To improve the performance and wellbeing of humans in complex human-computer interaction settings, an interesting challenge for an ambient (or pervasive) agent system is to recognise the emotions of humans. To this end, this paper introduces a computational model to estimate the process of emotion generation based on certain triggers. The model has been implemented and tested using the modelling language LEADSTO. A first evaluation indicates that the model is successful in estimating a person’s emotions, and is robust to different parameter settings. 1

Abstract. Both for developing human-like virtual agents and for developing intelligent systems that make use of knowledge about the emotional state of the user, it is important to model the mood of a person. In this paper, a model for simulating the dynamics of mood in human or human-like agents is presented. Psychological theories about a uni-polar clinical depression were used as a basis for inspiration and validation. A formal mathematical model is introduced that integrates several aspects of these existing theories. The model was analyzed both by simulations as mathematically, and it was shown that the model can describe how stress factors under some conditions can lead to a depression, while it won’t lead to a depression under other conditions. 1

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& Lesion and neuroimaging studies suggest the amygdala is important in the perception and production of negative emotion; however, the effects of emotion regulation on the amygdalar response to negative stimuli remain unknown. Using event-related fMRI, we tested the hypothesis that voluntary modulation of negative emotion is associated with changes in neural activity within the amygdala. Negative and neutral pictures were presented with instructions to either ‘‘maintain’ ’ the emotional response or ‘‘passively view’ ’ the picture without regulating the emotion. Each picture presentation was followed by a delay, after which subjects indicated how they currently felt via a response keypad. Consistent with previous reports, greater signal change was observed in the amygdala during the presentation of negative compared to neutral pictures. No significant effect of instruction was found during the picture presentation component of the trial. However, a prolonged increase in signal change was observed in the amygdala when subjects maintained the negative emotional response during the delay following negative picture offset. This increase in amygdalar signal due to the active maintenance of negative emotion was significantly correlated with subjects ’ self-reported dispositional levels of negative affect. These results suggest that consciously evoked cognitive mechanisms that alter the emotional response of the subject operate, at least in part, by altering the degree of neural activity within the amygdala. &

To develop a robot that is able to recognize and show affective behavior, it should be able to regulate simultaneously occurring tendencies of positive and negative emotions. To achieve this, the current paper introduces a computational model for involvement-distance trade-offs, based on an existing theoretical model. The main mechanisms of this model have been represented as regression equations, using the LEADSTO modeling environment. A number of simulation experiments have been performed, which indicated that the model is adequate for simulating the dynamics of involvement-distance trade-offs and their influence on satisfaction. More specifically, the experiments confirmed the empirical finding that positive features do not exclusively increase involvement.

Emotion regulation describes how a subject can use certain strategies to affect emotion response levels. Usually, models for emotion regulation assume mechanisms based on feedback loops that indicate how to change certain aspects of behaviour or cognitive functioning in order to get a more satisfactory emotion response level. Adaptation of such feedback loops is usually left out of consideration. In this paper, a model for adaptivity of emotion regulation is introduced. This model includes mechanisms for adaptivity of the degree of flexibility of the emotion regulation process. Based on this computational model, a number of simulation experiments have been performed and evaluated. 1.