Event-Driven Fuzzy Automata for Tracking Changes in the Emotional Behavior of Affective Agents

This paper proposes using a fuzzy state machine to model the transition process among different levels, ranging from extreme to neutral, for any given emotion. The fuzzy transition function of this automaton is based on a three dimensional analysis of the events that take place in the system. The Pleasure, Arousal and Dominance (PAD) evaluation vector encodes rich information about the levels of pleasure, arousal and dominance respectively that are associated with the occurred event. The proposed model demonstrates the construction of the full automaton for transitions over different emotional states. It further tracks the current emotional state of an individual after injecting a series of events to the system. The model ultimately identifies the most reliable transition sequence between a pair of given initial and final target states.