FLAME - Fuzzy logic adaptive model of emotions

Emotions are an important aspect of human intelligence and have been shown to play a significant role in the human decision-making process. Researcher s in areas such as cognitive science, philosophy, and artificial intelligen ce have proposed a variety of models of emotions. Most of the previous mode ls focus on an agent's reactive behavior, for which they often generate emo tions according to static rules or pre-determined domain knowledge. However , throughout the history of research on emotions, memory and experience hav e been emphasized to have a major influence on the emotional process. In th is paper, we propose a new computational model of emotions that can be inco rporated into intelligent agents and other complex, interactive programs. T he model uses a fuzzy-logic representation to map events and observations t o emotional states. The model also includes several inductive learning algo rithms for learning patterns of events, associations among objects, and exp ectations. We demonstrate empirically through a computer simulation of a pe t that the adaptive components of the model are crucial to users' assessmen ts of the believability of the agent's interactions.