Abstract

Abstract A major goal in various fields has been the development of believable, intelligent, and social Autonomous Agents (AAs) whose behavior is influenced by affective signals. This endeavor has promoted the development of cognitive architectures for AAs that incorporate processes that imitate those of human cognition and emotions. However, there is still a need for appropriate environments in such agent architectures for the modeling of the interaction between emotional and cognitive components. In this paper, we address the following research question: how to model the interaction of emotion and cognition in agent architectures so that AAs are capable of generating consistent emotional states and displaying believable emotional behaviors. We address this problem from the perspective of the development of Computational Models of Emotions (CMEs). In particular, we propose an integrative framework for constructing CMEs whose design is focused on two main aspects: (1) the modeling of the underlying mechanisms of emotions, and (2) the incorporation of input and output interfaces that facilitate the interaction between affective processes implemented in CMEs and cognitive processes implemented in agent architectures.

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