2005 Special Issue A systems approach to appraisal mechanisms in emotion (original) (raw)
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A systems approach to appraisal mechanisms in emotion
Neural Networks, 2005
While artificial neural networks are regularly employed in modeling the perception of facial and vocal emotion expression as well as in automatic expression decoding by artificial agents, this approach is yet to be extended to the modeling of emotion elicitation and differentiation. In part, this may be due to the dominance of discrete and dimensional emotion models, which have not encouraged computational modeling. This situation has changed with the advent of appraisal theories of emotion and a number of attempts to develop rule-based models can be found in the literature. However, most of these models operate at a high level of conceptual abstraction and rarely include the underlying neural architecture. In this contribution, an appraisal-based emotion theory, the Component Process Model (CPM), is described that seems particularly suited to modeling with the help of artificial neural network approaches. This is due to its high degree of specificity in postulating underlying mechanisms including efferent physiological and behavioral manifestations as well as to the possibility of linking the theoretical assumptions to underlying neural architectures and dynamic processes. This paper provides a brief overview of the model, suggests constraints imposed by neural circuits, and provides examples on how the temporal unfolding of emotion can be conceptualized and experimentally tested. In addition, it is shown that the specific characteristics of emotion episodes can be profitably explored with the help of non-linear dynamic systems theory. q
Advocating a componential appraisal model to guide emotion recognition
Most models of automatic emotion recognition use a discrete perspective and a black-box approach, i.e., they output an emotion label chosen from a limited pool of candidate terms, on the basis of purely statistical methods. Although these models are successful in emotion classification, a number of practical and theoretical drawbacks limit the range of possible applications. In this paper, the authors suggest the adoption of an appraisal perspective in modeling emotion recognition. The authors propose to use appraisals as an intermediate layer between expressive features (input) and emotion labeling (output). The model would then be made of two parts: first, expressive features would be used to estimate appraisals; second, resulting appraisals would be used to predict an emotion label. While the second part of the model has already been the object of several studies, the first is unexplored. The authors argue that this model should be built on the basis of both theoretical predictions and empirical results about the link between specific appraisals and expressive features. For this purpose, the authors suggest to use the component process model of emotion, which includes detailed predictions of efferent effects of appraisals on facial expression, voice, and body movements.
Assessing the validity of appraisal-based models of emotion
2009
Abstract We describe an empirical study comparing the accuracy of competing computational models of emotion in predicting human emotional responses in naturalistic emotion-eliciting situations. The results find clear differences in models' ability to forecast human emotional responses, and provide guidance on how to develop more accurate models of human emotion.
2001
The major assumptions of the appraisal approach to emotion, and progress in the development of two classes of models of emotion that embody this approach, are reviewed. The first class of model is structural and describes the relations between components of appraisal and components of the emotional response, such as subjective feeling state, facial actions, and autonomic activities. We present one prominent structural model, which describes the links between appraisal and the experience of distinct emotions. We also describe recent efforts to relate appraisal to specific facial actions and autonomic activities. The second class of model is procedural and describes the cognitive processes underlying emotion-eliciting appraisals. The major assumptions of one such model, currently under development, are described. Throughout this review, the functionality and coherence of the emotion system is emphasized.
Toward Modeling Emotion Elicitation Processes Using Fuzzy Appraisal Approach
This paper investigates using a fuzzy appraisal approach to model the dynamics for the emotion generation process of individuals. The proposed computational model uses guidelines from OCC emotion theory to formulate a system of fuzzy inferential rules that is capable of predicting the elicitation of different emotions as well as transitioning between different emotional states as a result of an occurred event, an action of self or other individuals, or a reaction to an emotion triggering object. In the proposed model, several appraisal variables such as event's desirability and expectedness, action's praise-worthiness and object's degree of emotional appealing were considered and thoroughly analyzed using different techniques. The output of the system is the set of anticipated elicited emotions along with their intensities. Results showed that the proposed computational model is a an effective and easy to implement framework that poses an acceptable approximation for the naturally sophisticated dynamics for elicitation and variation of emotional constructs in humans.
A Deep Neural Model Of Emotion Appraisal
ArXiv, 2018
Emotional concepts play a huge role in our daily life since they take part into many cognitive processes: from the perception of the environment around us to different learning processes and natural communication. Social robots need to communicate with humans, which increased also the popularity of affective embodied models that adopt different emotional concepts in many everyday tasks. However, there is still a gap between the development of these solutions and the integration and development of a complex emotion appraisal system, which is much necessary for true social robots. In this paper, we propose a deep neural model which is designed in the light of different aspects of developmental learning of emotional concepts to provide an integrated solution for internal and external emotion appraisal. We evaluate the performance of the proposed model with different challenging corpora and compare it with state-of-the-art models for external emotion appraisal. To extend the evaluation ...
Towards Emotion Classification Using Appraisal Modeling
International Journal of Synthetic Emotions, 2015
The authors studied whether a two-step approach based on appraisal modeling could help in improving performance of emotion classification from sensor data that is typically executed in a one-stage approach in which sensor data is directly classified into a (discrete) emotion label. The proposed intermediate step is inspired by appraisal models in which emotions are characterized using appraisal dimensions, and subdivides the task in a person-dependent and person-independent stage. In this paper, the authors assessed feasibility of this second stage: the classification of emotion from appraisal data. They applied a variety of machine learning techniques and used visualization techniques to gain further insight into the classification task. Appraisal theory assumes the second step to be independent of the individual. Results obtained are promising, but do indicate that not all emotions can be equally well classified, perhaps indicating that the second stage is not as person-independen...
A domain-independent framework for modeling emotion
2004
In this article, we show how psychological theories of emotion shed light on the interaction between emotion and cognition, and thus can inform the design of human-like autonomous agents that must convey these core aspects of human behavior. We lay out a general computational framework of appraisal and coping as a central organizing principle for such systems.
Computational modeling of emotion: Toward improving the inter-and intradisciplinary exchange
IEEE Transactions on Affective Computing, 2013
The past years have seen increasing cooperation between psychology and computer science in the field of computational modeling of emotion. However, to realize its potential, the exchange between the two disciplines, as well as the intradisciplinary coordination, should be further improved. We make three proposals for how this could be achieved. The proposals refer to: (1) systematizing and classifying the assumptions of psychological emotion theories; (2) formalizing emotion theories in implementation-independent formal languages (set theory; agent logics); and (3) modeling emotions using general cognitive architectures (such as Soar and ACT-R), general agent architectures (such as the BDI architecture) or generalpurpose affective agent architectures. These proposal share two overarching themes. The first is a proposal for modularization: deconstruct emotion theories into basic assumptions; modularize architectures. The second is a proposal for unification and standardization: Translate different emotion theories into a common informal conceptual system or a formal language, or implement them in a common architecture.
EMA: A process model of appraisal dynamics
COGNITIVE SYSTEMS RESEARCH, 2009
A computational model of emotion must explain both the rapid dynamics of some emotional reactions as well as the slower responses that follow deliberation. This is often addressed by positing multiple levels of appraisal processes such as fast pattern directed vs. slower deliberative appraisals. In our view, this confuses appraisal with inference. Rather, we argue for a single and automatic appraisal process that operates over a person's interpretation of their relationship to the environment. Dynamics arise from perceptual and inferential processes operating on this interpretation (including deliberative and reactive processes). This article discusses current developments in a computational model of emotion processes and illustrates how a single-level model of appraisal obviates a multi -level approach within the context of modeling a naturalistic emotional situation.