Machinery for artificial emotions

We present a preliminary definition and theory of artificial 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-ground ed basis. Affective appraisal is performed by the affective component of th e architecture; cognitive appraisal is performed by its cognitive component . A scheme for emotion classification with seven dimensions is presented. A mong them, we emphasize the roles played by emotions and the way these role s are fulfilled. It is shown how emotions are generated, represented, and u sed in the Salt & Pepper architecture for autonomous agents (Botelho, 1997) . Salt & Pepper is a specific architecture comprising an affective engine, a cognitive and behavioral engine, and an interruption manager. Most proper ties of the cognitive and behavioral engine rely upon a hybrid associative, schema-based long-term memory. In Salt & Pepper, emotion-signals, represen ted by label, object of appraisal, urgency, and valence, are generated by t he affective engine through the appraisal of the agent's global state. For each emotion-signal there are several nodes stored and interconnected in lo ng-term memory. Each of these nodes contains an emotion response that may b e executed when an emotion-signal is generated. Emotion intensity relates t o the activation of the node. It is shown that the Salt & Pepper architectu re for autonomous agents exhibits several properties usually related to emo tion: state and mood congruence, compound emotions, autonomic emotion-respo nses, and different emotion-responses to the same stimulus including the ge neration of different motives. The implementation of a concrete example is described.