Robotic Intuition Operation: A stimulus-object based hybrid approach to Emotional Modelling

Several computational models provide varying approaches to emotional modeling, e.g., event appraisal, motivational states, embodied robots, and data-driven. However, no model has wholly represented the complex emotional process, which calls for searching alternative ways. This paper proposes a simple hybrid computational model called RIO: Robotic Intuition Operation applicable in autonomous agents. Every event or object capable of emotional influence on an agent is classified as a stimulus having independent properties (including emotions and personality). An agent’s emotional state is defined as a set of six coexisting basic emotions (Ekman’s). Each perceived stimulus in a cycle independently deflects this emotional state towards its own (basic) emotions while considering the stimuli, other users, and the agent’s personality, trust, and likeness. The agent makes emotional decisions to support its primary goal and perform specific skills. Experiments and limitations follow the model’s novelty and discussion.