A Survey of Computational Emotion Research.
ABSTRACT Emotion reserch covers a multi-disciplinary domain. In the past three decades, a number of theoretical models and computer
applications have been proposed from different perspectives. There are models of appraisal theory, such as OCC and Frijda’s
model, as well as computational systems such as Affective Reasoner, EMA and Cathexis, to make agents believable and human-like.
This paper conducts a comprehensive analysis of those state-of-the-art based on the following six criteria, each of which
we believe represents a critical aspect in a computational emotion system.
Emotion Type Set. Each emotion model is explicitly or implicitly associated with a set of emotion types, each of which needs a clear characterization.
Different models may distinguish different types clearly from others, but it should explain as many as possible, which reflects
the adaptability for different emotions.
Emotion Simultaneity. According to psychology research, emotion is not a single and exclusive phenomenon. More than one emotion can arise simultaneously
within one emotion experiencer. The ability to handle this feature is important for compatibility.
Role-Orientedness. Human in society have one or more special positions, which are distinguished as social roles. People with different roles
may explain and respond to the same event differently, relying on which different emotions arise.
Emotion Situatedness. Most emotions may have an abstract definition or charac-terization. However, such definitions can not be used directly in
real-world applications for the gap between abstract characterizations and actual circumstances. A practical system needs
the ability to map daily emotional situations into general emotional rules.
Distributed Emotion. People do not live isolated in society. An individual will interact or have various relations with other people at times,
thus will influence the emotion response each other by speech and behavior, even by one’s own attitude and emotion state.
A broad model may deal with these factors and represent the emotions of the group.
Behavior Display. Following emotions, an individual may express some responses. Moreover, for a given emotional agent in the system, emotions,
together with the agent’s goals, may play a key role for the action selection of this agent.
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ABSTRACT: There is lack of researches on discovering the emotion communication patterns in turn level. It is believe that can give a new view to build emotion computing model and improve the emotion prediction performance for interactive texts based applications. In this paper, a hierarchical emotion category is given. Then a hierarchical sequential pattern mining method based on SPAM is proposed and used to mining the emotion communication patterns in turn level of Chinese interactive texts. Some interesting sequences are found and discussed.Proceedings of the 2010 14th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2010, April 14-16, 2010, Fudan University, Shanghai, China; 01/2010
Conference Paper: Emotion modeling in autonomic computing[Show abstract] [Hide abstract]
ABSTRACT: Autonomic unit is the essential element and the most basic component of autonomic systems. Having the ability of handling emotions is considered to make autonomic unit more intelligent, more communicative and more social. In this article we try to build an emotion model for agents that act as autonomic units in autonomic systems and can self-manage its behavior to achieve the best performance. From four levels we define four models progressively and the top-level model is defined on the foundation of the three below, combining them as a unity. By given arousing axioms theoretically of several typical emotions, the model is proved to be effective for reasoning emotions of autonomic unit, and can be easily extended for dealing with other type of emotions. On this base an architecture of emotional autonomic unit is described. An example shows that emotion plays an important role in intelligent decision making, which proves the validity of the model and the special function in practice.Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on; 07/2009