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The past two decades have witnessed a resurgence of interest in emotion research, as well as progress in understanding the circuitry that mediates affective processing in biological agents. Emotion researchers are now recognizing that computational models of emotion provide an important tool for understanding the mechanisms of affective processing. There has also been significant progress in affective computing technologies, including affective virtual agents, social robots and affect-adaptive human-computer interaction in general, including affective gaming and the associated desire to model more affectively realistic and believable agents and robots. This chapter describes a generic methodology for modeling emotions and their effects on cognitive processing. The methodology is based on the assumption that a broad range of both state and trait influences on cognition can be represented in terms of a set of parameters that control processing within the architecture modules. As such, the methodology is suitable both for exploring the nature of the mechanisms mediating cognition-emotion interaction and for developing more affectively realistic and believable agents and robots. An implementation of this generic methodology in a symbolic cognitive-affective architecture is described, focusing on an example of a research model. The chapter concludes with a discussion of open questions and challenges in affective modeling.
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- Modeling Cognition–Emotion Interactions in Symbolic Agent Architectures: Examples of Research and Applied Models
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