COMPUTATIONAL EMOTIONAL THINKING MODEL

International Journal of Synthetic Emotions, 2015

Turing genius anticipated current research in AI field for 65 years and stated that idea of intelligent machines “cannot be wholly ignored, because the idea of 'intelligence' is itself emotional rather than mathematical” (). This is the second article dedicated to emotional thinking bases. In the first article, the authors () created overall picture and proposed framework for computational emotional thinking. They used 3 bases for their work: AI - six thinking levels model described in book “The emotion machine” (). Evolutionary psychology model: “Wheel of emotions” (). Neuroscience (neurotransmission) theory of emotions by Lovheim “Cube of emotions” (). Based on neurotransmitters impact the authors proposed to model emotional computing systems. Current work is dedicated to three aspects left not described in first article: appraisal: algorithm and predicates - how inbound stimulus is estimated to trigger proper emotional response, coping: the way human treat with emotional ...

2007

Frontiers in Robotics and AI, 2016

International Journal of Software Science and Computational Intelligence, 2012

Emotions are one of the important subconscious mechanisms that influence human behaviors, attentions, and decision making. The emotion process helps to determine how humans perceive their internal status and needs in order to form consciousness of an individual. Emotions have been studied from multidisciplinary perspectives and covered a wide range of empirical and psychological topics, such as understanding the emotional processes, creating cognitive and computational models of emotions, and applications in computational intelligence. This paper presents a comprehensive survey of cognitive and computational models of emotions resulted from multidisciplinary studies. It explores how cognitive models serve as the theoretical basis of computational models of emotions. The mechanisms underlying affective behaviors are examined as important elements in the design of these computational models. A comparative analysis of current approaches is elaborated based on recent advances towards a ...

2012

Psychology researches are progressively showing however feeling plays an important role in psychological feature processes. Gradually, this information is getting used in Artificial Intelligent and Artificial Life areas in simulation and psychological feature processes modeling. However, theoretical aspects of feeling to use in procedure systems comes are scarcely mentioned and really few comparisons are created between comes. Besides, we can notice that there are several open queries emotion-based comes may face to field development. This paper intends to discuss these issues and suggest tentative directions to unravel them.

Lecture Notes in Computer Science, 2005

In last decades, neuroscience and psychology research findings about emotion have been increasingly attracting the attention of many researchers in Computer Science and Artificial Intelligence (AI) areas. AI, interested in cognitive processes modeling and simulation, clearly see that emotion is a crucial element to model perception, learning, decision processes, memory, behavior and others functions. Currently, two Computer Science areas use emotion concepts on their research: Human-Computer Interaction and systems whose internal architecture is emotion-based.Even considering current state-of-art projects, theoretical aspects of emotion to be employed in computational systems projects are scarcely discussed. Our research intends to discuss these problems and propose tentative directions to solve them.First, (ii) the lack of a well defined scientific framework to approach 'Artificial Emotion', with few advanced attempts been published suggesting one. Besides that, a close look at some projects provides a non-exhausted list of (ii) important questions they might face to achieve trustworthy results. They can be grouped in two types, theoretical-conceptual or computational questions. Examples are: How to integrate emotion with other mechanisms, such as: sensory, learn, selection and communication? Can artificial emotion be an emergent property? What kind of data structure and computational mechanisms should be used to both capture and represent the complexity of emotion processes? What kind of experimental test allows to better explore emotion-based models? Moreover, an essential question to be answered is related to which extent supposed structural complexity involved in emotion phenomenon can be abstracted and modeled, not missing important brain structure interactions and not being too complex to impair computational representation.Last, these facts mainly contribute to a third noticeable problem: (iii) lack of comparative analysis between projects and also within same project, with beneficial comparisons of emotion and non-emotion-based experiments. Positively, overcome these challenges can be an important step to field progress goes beyond engineering applications and towards a more scientific discipline.

Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011), 2011

—In this article, we introduce a computational model for the appraisal processes underlying emotion regulation from the perspective of Affect Control Theory. According to this theory, the affective meaning of emotions, behaviours, objects, and other entities can be assessed and projected onto a three dimensional space of evaluation, potency, and activity. This concept was applied to events occurring in the environment of an affective agent in order to study the dynamics of emotional changes caused by these events. Several appraisal processes were used to effectively analyze the affective impact of the occurred events and to interpret them in terms of the three dimensions of the affect control theory. A fuzzy automata framework was investigated and found to be a good fit to represent the dynamics of changes in the affective states and to effectively picture the transitions between different emotional response levels. Based on the results obtained from conducted experiments, we can argue that the proposed model has the potential to be used in predicting the emotional changes in (human/virtual) agents as a result of the occurrence of emotion-triggering events. Furthermore, it would appear that the proposed model has the capability to be used as the kernel of an extended system developed for reverse engineering events, and to generate and apply those in-favor of emotion regulation process.