The emergence of what is now called ‘emotional intelligence’ has revealed yet another aspect of human intelligence. Emotions have been shown to have a major impact on many of our everyday functions, including decision-making, planning, communication, and behavior. AI researchers have recently acknowledged this major role that emotions play, and thus have began to incorporate models for simulating emotions into agents. However, the emotional process is not a simple process; it is often linked with many other processes, one of which is learning. It has long been emphasized in psychology that memory and experience help shape the dynamic nature of the emotional process. In this paper, we introduce PETEEI (a PET with Evolving Emotional Intelligence). PETEEI is based on a fuzzy logic model for simulating emotions in agents, with a particular emphasis on incorporating various learning mechanisms so that an agent can adapt its emotions according to its own experience. Additionally, PETEEI is designed to recognize and cope with the various moods and emotional responses of its owner. A user evaluation experiment indicated that simulating the dynamic emotional process through learning provides a significantly more believable agent.
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