Toward integrating cognitive components with computational models of emotion using software design patterns

Computational models of emotion (CMEs) are software systems designed to imitate particular aspects of human emotions. The main purpose of this type of computational model is to capture the complexity of the human emotion process in a software system that is incorporated into a cognitive agent architecture. However, creating a CME that closely imitates the actual functioning of emotions demands to address some challenges such as (i) sharing information among independently developed cognitive and affective components, and (ii) interconnecting complex cognitive and affective components that must interact with one another in order to generate realistic emotions, which may even affect agents’ decision making. This paper proposes an architectural pattern aimed at cataloging and describing fundamental components of CMEs and their interrelationships with cognitive components. In this architectural pattern, external cognitive components and internal affective components of CMEs do not interact directly but are extended by including message exchange methods in order to use a publish-subscribe channel, which enables their intercommunication, thus attenuating issues such as software heterogeneity. This structural approach centralizes communication management and separates the inherent complexity of the cognitive and affective processes from the complexity of their interaction mechanisms. In so doing, it enables the design of CMEs’ architectures composed of independently developed affective and cognitive components. The proposed architectural pattern attempts to make progress in capturing the complex process of human emotions in a software system that adheres to software engineering best practices and that incorporates quality attributes such as flexibility and interoperability.     

A general theoretical framework for the design of artificial emotion systems in Autonomous Agents

Autonomous Agents (AAs) capable of exhibiting emotional behaviors have contributed to the development of natural human-machine interactions in several application domains. In order to provide AAs with emotional mechanisms, their underlying architecture must implement an Artificial Emotion System (AES), a computational model that imitates specific facets of human emotions. Although several AES have been reported in related literature, their design is generally supported on several emotion theories, leading researchers to model and integrate isolated emotion components and mechanisms into the architectures of AES. This theoretical foundation of AES contributes to ambiguities in the analysis and comparison of their underlying architectures, which demands the definition of standards, design guidelines, and integrative frameworks. In this paper, we present a psychologically inspired theoretical framework designed to serve as a platform for the unification of AES' components, the comparison of AES, and the design and implementation of AES in AAs. We analyze common emotion-related requirements of AES, emotion components involved in the design of this type of computational model, and emotion theories that drive the design of most AES. The validation of this framework demonstrates its compatibility with current AES and its feasibility as a model for unifying multiple emotional theories.     

Modeling of emotion elicitation conditions for a cognitive-emotive architecture

To cater to the need of embodying emotional behavior in an autonomous agent, there is a need for modeling computationally apt definitions of emotions. A number of emotion theories have been developed that provide an understanding of human psychology and their emotional behaviors, but it is difficult to directly decipher a theory into a computational model of emotion. Nevertheless, these theories together can serve as the theoretical foundation for designing a model for emotion-eliciting conditions. In this study, the salient features of OCC, Scherer, and Roseman theories of emotions are identified, which complement each other. The features are unified and standardized to bring consistency in deriving the computationally apt definition of five emotions viz. Happiness/Joy, Sadness, Fear, Anger, and Surprise. The objective of this hybridization is to set a ground framework for appraising the emotion-triggering cues (e.g., an event) for a simple, flexible and tolerant computational model of emotions. The underlying emotion-eliciting processes are designed using Fuzzy Logic. Fuzzy rules are framed to model the conditions behind emotion elicitation. Furthermore, the ISEAR data set and the real test-case scenarios are used to validate the accuracy of emotion prediction and rule fulfillment respectively.     

Infants and Emotions: How the Ancients' Theories Inform Modern Issues

Although cognitively oriented theories of emotion are now dominant in the psychological study of emotion, there remain issues upon which these theories do not agree. Central among these are questions regarding the minimal cognitive processes necessary to have an emotion. A potentially productive approach to such questions is the study of the relation of cognitive development and the development of emotions in infants. Such an approach was featured in ancient philosophical and psychological treatises, some of which formed the very foundations of later cognitive theories. However, the recent literature has been nearly indifferent to just these foundations. Ancient commentators, especially Aristotle and the Stoic and Epicurean philosophers, understood emotions as fundamentally sociomoral constructs. Owing to a lack of socialisation and moral understanding, infants are not fully capable of experiencing emotions as they are typically understood. Contemporary work in the area of emotion, including that of Michael Lewis, as well as work in other emotion-related areas, is shown to address only inadequately the sociomoral components of emotion and thus to address only inadequately the emotion-cognition relationship.     

Functional Accounts of Emotions

In this article we outline the history, elements, and variations of functional accounts of emotions. Summarising diverse theories and observations, we propose that functional accounts of emotions: (1) address why humans have emotions; (2) define emotions as solutions to problems and opportunities related to physical and social survival; (3) treat emotions as systems of interrelated components; and (4) focus on the beneficial consequences of emotions. This conceptual approach to emotion is complemented by several empirical strategies, including the study of emotion dysfunction, the effects of emotions on others, and the relations between emotions and personal and social outcomes. We conclude by considering how functional accounts of emotion vary, including in terms of their level of analysis, specificity, manner of organisation, and range of focus, and the implications functional accounts have for the study of emotion.     

Appraisal of Emotions in Media Use: Toward a Process Model of Meta-Emotion and Emotion Regulation

Over the past 20 years, research on meta-emotion and related concepts such as meta-mood and need for affect has become fruitful and prominent across a variety of disciplines, including media psychology. This paper reviews the literature on meta-emotion and considers problems regarding the definition and operationalization of this construct. We propose a process model of meta-emotion and emotion regulation to integrate and extend existing work. Drawing on appraisal theories of emotion, we understand meta-emotion as a process that monitors and appraises emotions and recruits affective responses toward them, which results in a motivation to maintain and approach emotions, or to control and avoid them. This meta-emotion process plays an important role in media users' selection or rejection of specific media offerings and their invitation to experience emotion. We discuss how this framework may integrate previously unrelated findings on the role of emotions in guiding selective media use and conclude with directions for further research.     

Group-based emotions as determinants of ingroup identification

Events affecting an ingroup with which one identifies trigger group-based emotions. Thus, identification with a group seems to be a crucial determinant of group-based emotions. However, some theories (e.g., Russell, 2003) suggest bi-directional causal links between components of emotions. The current research examines whether group-based emotions may also influence ingroup identification. In a study, type of emotion (happiness vs. anger) and object of emotion (ingroup vs. outgroup) were manipulated. The results show an interaction effect of type of emotion and object of emotion on change in ingroup identification. Identification increases with happiness towards the ingroup or anger towards the outgroup, whereas identification decreases with anger toward the ingroup and happiness toward the outgroup. Moreover, the intensity of emotions determines the degree of change in identification. The implications for approaches of group-based emotions are discussed.     

Can the uncertainty appraisal associated with emotion cancel the effect of the hunch period in the Iowa Gambling Task?

Research has given little attention to the influence of incidental emotions on the Iowa Gambling Task (IGT), in which processing of the emotional cues associated with each decision is necessary to make advantageous decisions. Drawing on cognitive theories of emotions, we tested whether uncertainty-associated emotion can cancel the positive effect of the hunch period, by preventing participants from developing a tendency towards advantageous decisions. Our explanation is that uncertainty appraisals initiate deliberative processing that is irrelevant to process emotional cues, contrary to intuitive processing (Kahneman, 2003; Tiedens & Linton, 2001). As expected, uncertainty-associated emotion cancelled the positive effect of the hunch period in the IGT compared to certainty-associated emotion: disgusted participants (certainty-associated emotion) and sad participants induced to feel certainty developed a stronger tendency towards advantageous decisions than sad participants induced to feel uncertainty. We discuss the importance of the core components that trigger incidental emotions to predict decision making.     

The structure of emotion: An empirical comparison of six models

There are a number of conflicting approaches to the problem of the relationship between different emotions. One category of models focuses on the valence of emotional experience and typically reports evidence for dimensional approaches to emotion. A second category of models argues for the possibility of discrete basic emotions, but typically focuses on evidence from emotion systems other than conscious experience. In the present study, a list of emotion terms was drawn up that were derived conceptually from a set of basic emotions. A group of participants filled out a questionnaire that asked how much in general they experienced each of the emotions. A structural equation modelling approach was then used with the resultant dataset, an approach that permitted the comparison of six different models that ranged from the positive-negative affect models to models of discrete basic emotions. The analyses gave support for a set of five basic emotions but only when these were allowed to correlate with each other. Implications for theories of emotion are considered.     

Implicit theories of emotion: affective and social outcomes across a major life transition

The authors demonstrate that people differ systematically in their implicit theories of emotion: Some view emotions as fixed (entity theorists), whereas others view emotions as more malleable (incremental theorists). Using a longitudinal and multimethod design, the authors show that implicit theories of emotion, as distinct from intelligence, are linked to both emotional and social adjustment during the transition to college. Before entering college, individuals who held entity (vs. incremental) theories of emotion had lower emotion regulation self-efficacy and made less use of cognitive reappraisal (Part 1). Throughout their first academic term, entity theorists of emotion had less favorable emotion experiences and received decreasing social support from their new friends, as evidenced by weekly diaries (Part 2). By the end of freshman year, entity theorists of emotion had lower well-being, greater depressive symptoms, and lower social adjustment as indicated in both self- and peer-reports (Part 3). The emotional, but not the social, outcomes were partially mediated by individual differences in emotion regulation self-efficacy (Part 4). Together, these studies demonstrate that implicit theories of emotion can have important long-term implications for socioemotional functioning.     

Exploring and integrating discrete and dimensional approaches while inducing negative emotional states

Selecting visual stimuli for inducing specific emotional states is very challenging, since the choice relies on specific conceptualization of emotions. In this work, we present a set of 55 stimuli, realized integrating discrete and dimensional theories of emotions, and specifically selected to investigate anger, fear, and disgust reactions in non-clinical and clinical contexts. Our set of stimuli presents several aspects of novelty since (1) a large and heterogeneous sample of subjects from the general population was involved in the labelling task, and (2) bivariate and multivariate statistical techniques were applied to integrate emotion models. The proposed set of stimuli could be useful for researchers and other professionals in the affective sciences to address negative emotion recognition issues within a broader perspective both in general population and in psychiatric samples. The obtained comprehensive characterization of the stimuli allowed us to confirm the sexual dimorphism in emotional processing.     

情绪设计对多媒体学习的影响

通过两个实验探讨多媒体学习中情绪设计对学习者情绪、认知过程和学习结果的影响。实验1将内部情绪设计与外部情绪诱发两种方式结合起来,探讨多媒体学习环境中不同方式诱发的积极情绪对学习的影响。实验2进一步聚焦于内部情绪设计,考察颜色和拟人化这两个特定的情绪设计元素对学习者情绪和学习的影响。结果发现:(1)积极的外部情绪诱发和内部情绪设计可以诱发积极情绪,并促进学习迁移。(2)对学习材料进行内部积极情绪设计可以诱发学习者积极情绪,增强学习者的学习动机,降低学习者感知到的学习材料的难度,并促进学习迁移。其中,彩色设计可以诱发学习者积极情绪,但拟人化只有与彩色结合才能诱发学习者积极情绪;在拟人化条件下,彩色设计可以增强学习者学习动机;彩色设计可降低学习者对学习材料感知到的难度;彩色和拟人化都可以促进学习迁移。     

Collective emotions

Research on collective emotions has been limited until recently to theories of irrational crowds, scepticism about genuinely group‐level psychological phenomena and analyses of the unconscious or ritual sources of mass affective experience. However, collective emotion is now a thriving research area that combines studies from philosophy, anthropology, sociology, social psychology and neuroscience. This article examines neo‐Durkheimian theories of collective emotions and relevant contributions of discursive psychologists and other social scientists influenced by the “turn to affect.” I argue that future theoretical and empirical investigations should do the following: (1) critically examine theories focusing on diffuse emotional energy and discrete collective emotions by also exploring the generation and production of genuinely collective mixed emotions; (2) clarify problems with “bottom‐up” models of causal mechanisms through exploration of “affective practices”; and (3) explore the implications of Tuomela's ( 2013 ) “top‐down” social ontology of “group agents” as a framework for theories and studies of collective emotion.     

Appraisal,computational models,and scherer's expert system

Abstract

This paper discusses computational models of the mechanism of emotion elicitation according to appraisal theories of emotion. Following a brief review of earlier models, the general affordances of computational models are discussed. Scherer's (1993) recent “expert system” for predicting emotions is then examined in some detail, followed by an exploration of several alternative algorithms for computing an elicited emotion based on an appraisal specification.     

Précis of The brain and emotion

The topics treated in The brain and emotion include the definition, nature, and functions of emotion (Ch. 3); the neural bases of emotion (Ch. 4); reward, punishment, and emotion in brain design (Ch. 10); a theory of consciousness and its application to understanding emotion and pleasure (Ch. 9); and neural networks and emotion-related learning (Appendix). The approach is that emotions can be considered as states elicited by reinforcers (rewards and punishers). This approach helps with understanding the functions of emotion, with classifying different emotions, and in understanding what information-processing systems in the brain are involved in emotion, and how they are involved. The hypothesis is developed that brains are designed around reward- and punishment-evaluation systems, because this is the way that genes can build a complex system that will produce appropriate but flexible behavior to increase fitness (Ch. 10). By specifying goals rather than particular behavioral patterns of responses, genes leave much more open the possible behavioral strategies that might be required to increase fitness. The importance of reward and punishment systems in brain design also provides a basis for understanding the brain mechanisms of motivation, as described in Chapters 2 for appetite and feeding, 5 for brain-stimulation reward, 6 for addiction, 7 for thirst, and 8 for sexual behavior.     

Indirect scaling methods for testing quantitative emotion theories

Two studies investigated the utility of indirect scaling methods, based on graded pair comparisons, for the testing of quantitative emotion theories. In Study 1, we measured the intensity of relief and disappointment caused by lottery outcomes, and in Study 2, the intensity of disgust evoked by pictures, using both direct intensity ratings and graded pair comparisons. The stimuli were systematically constructed to reflect variables expected to influence the intensity of the emotions according to theoretical models of relief/disappointment and disgust, respectively. Two probabilistic scaling methods were used to estimate scale values from the pair comparison judgements: Additive functional measurement (AFM) and maximum likelihood difference scaling (MLDS). The emotion models were fitted to the direct and indirect intensity measurements using nonlinear regression (Study 1) and analysis of variance (Study 2). Both studies found substantially improved fits of the emotion models for the indirectly determined emotion intensities, with their advantage being evident particularly at the level of individual participants. The results suggest that indirect scaling methods yield more precise measurements of emotion intensity than rating scales and thereby provide stronger tests of emotion theories in general and quantitative emotion theories in particular.     

决策中情绪作用机制的理论研究述评

决策研究领域日益重视情绪的作用,情绪的认知评估理论、道德情绪理论及动机维度模型等新兴情绪观使研究者对决策机制的认识不断深化,出现了解释情绪在各类决策中作用机制的理论成果：情绪浸润模型、风险决策感知与评估双系统模型、情绪即社会信息模型、神经情感决策理论。未来尚需加强作用机制的验证研究,从情绪具身角度进行思考,基于知情交互的角度整合理论体系,重视神经生理机制理论及模型建构。并简要分析了理论成果的启示。     

Contemplative/emotion training reduces negative emotional behavior and promotes prosocial responses

Contemplative practices are believed to alleviate psychological problems, cultivate prosocial behavior and promote self-awareness. In addition, psychological science has developed tools and models for understanding the mind and promoting well-being. Additional effort is needed to combine frameworks and techniques from these traditions to improve emotional experience and socioemotional behavior. An 8-week intensive (42 hr) meditation/emotion regulation training intervention was designed by experts in contemplative traditions and emotion science to reduce "destructive enactment of emotions" and enhance prosocial responses. Participants were 82 healthy female schoolteachers who were randomly assigned to a training group or a wait-list control group, and assessed preassessment, postassessment, and 5 months after training completion. Assessments included self-reports and experimental tasks to capture changes in emotional behavior. The training group reported reduced trait negative affect, rumination, depression, and anxiety, and increased trait positive affect and mindfulness compared to the control group. On a series of behavioral tasks, the training increased recognition of emotions in others (Micro-Expression Training Tool), protected trainees from some of the psychophysiological effects of an experimental threat to self (Trier Social Stress Test; TSST), appeared to activate cognitive networks associated with compassion (lexical decision procedure), and affected hostile behavior in the Marital Interaction Task. Most effects at postassessment that were examined at follow-up were maintained (excluding positive affect, TSST rumination, and respiratory sinus arrhythmia recovery). Findings suggest that increased awareness of mental processes can influence emotional behavior, and they support the benefit of integrating contemplative theories/practices with psychological models and methods of emotion regulation.