Simulating Synthetic Emotions with Fuzzy Grey Cognitive Maps

Autonomous robotic systems should decide autonomously without or with sparse human interference how to react to alterations in environment. Based on Thayer’s emotion model and Fuzzy Grey Cognitive Maps, this work presents a proposal for simulating synthetic emotions. Thayer’s proposal is based on mood analysis as a bio psychological concept. Recently, Fuzzy Grey Cognitive Maps have been proposed as a FCM extension. FGCM is mixing conventional Fuzzy Cognitive Maps and Grey Systems Theory that has become a worthy theory for solving problems with high uncertainty under discrete small and incomplete data sets. This proposal provides an innovative way for simulating synthetic emotions and designing an affective robotics system. This work includes an experiment with an artificial scenario for testing this proposal.