A Fuzzy Logic Computational Model for Emotion Regulation Based on Gross

Emotion regulation looks into methods and strategiesthat humans use in order to control and balance theirpossible extreme levels of emotions. One importantchallenge in building a computational model of emotionsis the mainly non-quantitative nature of this problem.In this paper, we investigate a Fuzzy logic approachas a possible framework for providing the requiredqualitative and quantitative description of suchmodels. In our proposed fuzzy computational modelwhich was constructed based on Gross theory for emotionregulation, beside the fuzzy structure, it includesa learning module that enhances the model adaptivityto environmental changes through learning some relevantaspects such as patterns of events’ sequences. Theresults of the simulation experiments were comparedagainst a formerly presented non-fuzzy implementation.We observed that the agents in our proposed modelmanaged to cope better with changes in the environmentand exhibited smoother regulation behavior. Moreover,our model showed further consistency with the inferentialrules of Gross theory.