Machinery for Artificial Emotions

We present a preliminary definition and a theory of emotion viewed as a sequential process comprising the appraisal of the agent global state, the generation of an emotion-signal and an emotion-response. This theory distinguishes cognitive from affective appraisal on an architecture-grounded basis. A scheme for emotion classification with five dimensions is presented. Among them, we emphasize the roles played by emotions and the way these roles are fulfilled. It is shown how emotions are generated, represented and used in the Salt & Pepper architecture for autonomous agents [Botelho 1997]: emotion-signals, represented by label, valence and intensity, are generated by the affective engine through the appraisal of the agent's global state; for each emotion-signal there are several nodes stored and interconnected in the behavioral or in the cognitive networks of the agent; each of these nodes contains an emotion response that may be executed when an emotion-signal is generated; emotion intensity relates to the activation of the node. The implementation of a concrete example is fully described.