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.     

Investigating a process model for leader affective presence,interpersonal emotion regulation,and interpersonal behaviour in teams

Leader affective presence is the tendency of leaders to elicit feelings that are consistent among other individuals, and has been supported as a relevant personality trait for understanding teamwork. Drawing on a model that integrates personality and emotion regulation, this study aimed to expand research on affective presence by proposing team members’ perceptions of leader interpersonal emotion regulation as a process that explains how leader affective presence is related to team member behaviour. In the model, teamness—the perception that interdependence and reflexivity are required in the team—is presented as a boundary condition to the effects of affective presence via emotion regulation. Results of a study conducted with 99 teams showed that team member ratings of leader positive affective presence were linked to their perceptions that leaders had used affect-improving emotion regulation which in turn was associated with greater team citizenship behaviour. Contrariwise, team member ratings of leader negative affective presence were associated with perceived use of affect-worsening emotion regulation by leaders which in turn was associated with lower levels of team citizenship, but only when teams were low in teamness. These findings contribute to understanding how leaders’ individual differences are related to teamwork through affective processes.     

The appraisal process: Exploring the role of meaning,importance, control and coping in work stress

Recent reviews on occupational stress research suggests that if progress is to be made towards a better understanding of stress at work then researchers need to consider alternative methodologies and establish new frameworks. This paper takes up that challenge and using both quantitative and qualitative techniques attempts to explore the appraisal process individuals go through in determining stressful experiences. The meanings individuals give to events, their importance and individual levels of control all provide fruitful avenues for further research. Such variables provide new approaches to research and offer a potential for explanation far greater than the more traditional interactional models.     

Progress in the development of a multidimensional measure of fear of failure: The performance failure appraisal inventory (pfai)

Abstract

Measuring fear of failure (FF) is a tremendous challenge for researchers and practitioners because (a) existing measures have demonstrated limited support for the validity of their score interpretations, and (b) existing measures are unidimensional while accumulating evidence suggests that FF is multidimensional. The Performance Failure Appraisal Inventory (PFAI) was developed to measures a set of empirically-derived congnitive-motivational-relational appraisals associated with FF. Results indicated that PFAI scores represented fears of (a) experiencing shame and embarrassment, (b) devaluing one's self-estimate, (c) losing social influence, (d) having an uncertain future, and (e) upsetting important others. Correlations with external measures of achievement goal orientations, trait anxiety, and social desirability were consistent with theoretical predictions. PFAI scores correctly classified 76.5% of participants' perceptions of underachievement.     

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.     

Blind spots in the search for happiness: Implicit attitudes and nonverbal leakage predict affective forecasting errors

We investigated implicit knowledge and affective forecasting, reasoning that although conscious evaluations are available to people when predicting their future emotional responses, nonconscious evaluations are not. However, these automatically-activated evaluations should contribute to in-the-moment emotional experiences, and thus they should account for misforecasts (i.e., discrepancies between affective forecasts and actual experiences). We conducted two studies to explore affective misforecasts, using food items as stimuli. In Study 1, participants' implicit attitudes (but not their explicit attitudes) predicted misforecasts of food enjoyment, supporting the role of nonconscious evaluations in affective forecasting errors. In Study 2, we examined participants' facial expressions (another index of nonconscious evaluation) upon the presentation of food items, and we found that these nonverbal behaviors predicted affective misforecasts as well. In sum, although nonconscious evaluations are unavailable when anticipating the future, they may contribute to one's in-the-moment experiences and thus serve as blind spots in affective forecasting.     

Development of computational models of emotions: A software engineering perspective

Computational Models of Emotions (CMEs) are software systems designed to explain the phenomenon of emotions. The mechanisms implemented in this type of computational models are based on human emotion theories reported in the literature and designed to provide intelligent agents with affective capabilities and improve human-computer interaction. However, despite the growing interest in this type of models, the development process of CMEs does not seem to follow formal software methodologies. In this paper, we present an analysis of CMEs from a software engineering perspective. We aim to identify what elements of software engineering are used in the development process of CMEs and to demonstrate how some software engineering techniques may support and improve their development process. We discuss a series of challenges to be addressed in order to take advantage of software engineering techniques: (1) definition of guidelines to help decide which emotion theories should be implemented computationally, (2) homogenization of terms about human emotions, their components, phases, and cycles implemented in CMEs, (3) design of CMEs whose components can be reusable, (4) definition of standard criteria for comparative analysis between CMEs, (5) identification of software engineering principles, concepts, and design practices useful in the construction of CMEs, and (6) definition of standard frameworks to validate CMEs.     

A comparison of retrospective self-report versus ecological momentary assessment measures of affective lability in the examination of its relationship with bulimic symptomatology

Affective lability has been linked to several maladaptive behaviors ( [Anestis et?al., 2009] and [Coccaro, 1991]). Methodology for measuring affective lability varies and includes retrospective self-report and ecological momentary assessment (EMA). In this study, we sought to test these methodologies by examining which better predicted binge eating episodes and general eating disorder symptoms in a sample (n = 131) of women diagnosed with bulimia nervosa (BN). We hypothesized that, while the two forms of measurement would be correlated with one another and predict binge eating episodes, EMA affective lability would be the stronger predictor. Results supported several hypotheses. Specifically, both EMA affective lability and retrospective self-report affective lability significantly predicted global eating disorder symptoms, even when controlling for depression, age, body mass index, and level of education, EMA affective lability exhibited a significantly stronger correlation with binge eating episodes than did retrospective self-report affective lability, and EMA affective lability predicted number of binge eating episodes on any given day controlling for the same list of covariates. Limitations include the use of a clinical sample that may limit the generalizability of our findings. Findings highlight the importance of affect in such behavior.     

A cognitive architecture for modeling emotion dynamics: Intensity estimation from physiological signals

Current approaches to emotion recognition do not address the fact that emotions are dynamic processes. This work concerns itself with the development of a cognitive architecture for modeling the dynamics of emotions with specific focus on a gray-box model for dynamic emotion intensity estimation that can incorporate findings from appraisal models, specifically Scherer’s Component Process Model. It is based on Dynamic Field Theory which allows the combination of theoretical knowledge with data-driven experimental approaches. A user study is conducted applying the proposed model to estimate intensity of negative emotions from physiological signals. Results show significant improvements of the proposed model to common methodology and baselines. The flexible cognitive architecture opens a wide field of experiments and directions to deepen the understanding of emotion processes as a whole.     

Effects of intergroup and interpersonal context, and individuals' appraisal of their in-group on the intragroup comparison process

The present study examined whether individuals' endorsement of intergroup context moderates the social comparison process not only in the intergroup upward comparison condition, but also in the downward comparison condition, by experimentally manipulating the direction of intergroup comparison and interpersonal comparison for participants who appraise their in-group as high or low. As predicted, participants who appraise their in-group as high showed reflection processes in the intergroup upward comparison condition, but comparison processes in the intergroup downward comparison condition because of their endorsement of their in-group position. In contrast, participants who appraised their in-group as low showed comparison processes in the intergroup upward comparison condition, but reflection processes in the intergroup downward comparison condition. These results imply that the interplay between intergroup context and individuals' internal factors affect intragroup comparison processes.     

The importance of identifying underlying process abnormalities in alexithymia: Implications of the three-process model and a single case study illustration

We present an in-depth case study of a rare individual (whom we will refer to as “Jane”) who reported an inability to experience emotion. Jane completed a range of assessments measuring alexithymia, emotional awareness, and emotion recognition ability. She, along with 22 control participants, also underwent skin conductance (SC) measurement and facial electromyography (EMG) during exposure to affective images, and self reported the valence/arousal of their responses to those images. Jane scored high on alexithymia and low on emotional awareness; yet she performed well on emotion recognition measures and showed a typical pattern of valence ratings. Her SC responses and subjective arousal ratings were atypically low, and some of her EMG responses were also atypical. Jane’s deficit profile highlights the dissociability of self-focused emotional awareness and other-focused emotion recognition ability, as well as the dissociability between the generation and representation of valence and arousal (with both subjective and objective measures).     

Video playback,affective witnessing,and the mobility of trauma: Video evidence of violent crime in the criminal justice system

In today's technologically mediated society, video is increasingly relied upon as an objective and reliable source of evidence in the investigation and prosecution of violent crimes. The now pervasive presence of violent video in the criminal justice system, however, presents new challenges for understanding repeated work-related exposure to and witnessing of potentially traumatic material and its impacts. Thus, this project seeks to qualitatively examine the relational affective processes that occur among criminal justice professionals when violent crimes are captured on video. We present four key categories organized around the circumstances of exposure and its impacts: 1) playback in the investigative and pre-trial process; 2) sharing videos among colleagues; 3) playing videos for victims, witnesses, and families and; 4) transmission in the broader public. Findings suggest this work involves deeply embodied processes where video evidence of violent crime enables a virtual presence at scenes and an emotional proximity to events through new forms of witnessing. These affective experiences are one relational dynamic that keeps witnessing active, thus expanding the mobility of trauma, its reach and potential impacts.     

A latent topic model with Markov transition for process data

We propose a latent topic model with a Markov transition for process data, which consists of time-stamped events recorded in a log file. Such data are becoming more widely available in computer-based educational assessment with complex problem-solving items. The proposed model can be viewed as an extension of the hierarchical Bayesian topic model with a hidden Markov structure to accommodate the underlying evolution of an examinee's latent state. Using topic transition probabilities along with response times enables us to capture examinees' learning trajectories, making clustering/classification more efficient. A forward-backward variational expectation-maximization (FB-VEM) algorithm is developed to tackle the challenging computational problem. Useful theoretical properties are established under certain asymptotic regimes. The proposed method is applied to a complex problem-solving item in the 2012 version of the Programme for International Student Assessment (PISA).     

他人财富情绪:妒忌的社会评估比较与认知加工分析

妒忌是指意识到自己缺乏他人更优越的品质、成就或所有物而产生的自卑、敌意和怨恨等混合情绪,妒忌者渴望得到妒忌目标的优势或希望妒忌目标失去优势。作为一种指向他人财富的复杂情绪,善意妒忌和恶意妒忌会引发不同的行为结果,这主要取决于个体对他人财富的认知评估过程。妒忌通常由向上的社会比较而产生,社会事件应得性、主观公平感、核心自我评价等认知都会对妒忌产生影响。本文从社会比较判断、认知加工过程和神经生理功能等角度来分析妒忌的产生过程和认知机制。基于现有不足,未来的研究可以在妒忌情绪的发展特征、妒忌体验的测量方法和妒忌功能的分化等方面进一步完善。     

High regularities in eye-movement patterns reveal the dynamics of the visual working memory allocation mechanism

With only two to five slots of visual working memory (VWM), humans are able to quickly solve complex visual problems to near optimal solutions. To explain the paradox between tightly constrained VWM and impressively complex human visual problem-solving ability, we propose several principles for dynamic VWM allocation. In particular, we propose that complex visual information is represented in a temporal manner using only a few slots of VWM that include global and local visual chunks. We built a model of human traveling salesman problem solving based on these principles of VWM allocation and tested the model with eye-movement data. Exactly as the model predicted, human eye movements during traveling salesman problem solving have precise quantitative regularities with regard to both the general statistical pattern of attentional fixations and how they vary across individuals with different VWM capacities. Even though VWM capacity is very limited, eye movements dynamically allocate VWM resources to both local and global information, enabling attention to fine details without loss of the big picture.     

A processing model for the analysis of one-way arguments in discourse

This paper describes a computational model for analyzing arguments in discourse. In particular, the model describes processes necessary for interpreting one uninterrupted argument from a speaker. The resulting output is a representation for the underlying claim and evidence relations between propositions of the argument. For our processing model we present: (i) a characterization of coherent orderings of propositions, used to limit search for interpretation of each new proposition (ii) a working definition of the evidence relation, used to recognize connections between propositions (iii) a theory of the function and use of clue words — special words and phrases indicating the structure of the argument — then used in the analysis to control search for interpretation and verification of evidence relations.     

自恋型领导对团队创造力形成过程的多视角研究

领导自恋是组织中的普遍现象, 自恋型领导是否能有效地整合团队知识形成创新是管理者不可回避的问题。在回顾已有研究基础上, 采用聚合观、过程观和社会网络三种视角, 全面地厘清自恋型领导对团队创造力的影响。其中, 聚合观强调个体创造力对形成团队创造力的重要作用, 过程观强调团队成员之间的交互作用在团队创造力形成过程中不可或缺, 而社会网络视角注重团队成员的相对位置和内外关系。三种视角相互补充, 明确了自恋型领导和团队创造力之间关系的内在机制以及边界条件。研究结论将为存在自恋型领导的团队干预策略提供参考, 有助于为管理者提高自恋型领导对团队作用的有效性提供借鉴。     

A dual-process model of affective and instrumental attitudes in predicting physical activity

IntroductionA novel dual-process model based upon the affective-reflective theory which distinguishes between affective attitude and instrumental attitude at an explicit and implicit level was used to predict physical activity.MethodUndergraduate students (N = 114) completed a lab-based study at two time-points, spaced two weeks apart. Participants completed self-report measures of the theory of planned behavior constructs, including explicit affective attitude and explicit instrumental attitude. Implicit affective attitude and implicit instrumental attitude were measured using single category implicit association tests.ResultsExplicit affective attitude and perceived behavioral control indirectly predicted physical activity through intention, and explicit affective attitude, implicit affective attitude, and intention predicted physical activity directly with a modest effect size (R² = 0.24).DiscussionFindings suggest explicitly and implicitly held evaluative information are conceptually distinct, and affective evaluations are key in guiding physical activity behavior regardless of whether such evaluations are implicit or consciously accessible.