Emotions in Collective Risk Dilemmas Using Fuzzy Linguistic Rules

The goal of this paper is to propose how to model emotions in climate change policies through evolutionary game theory (i.e., collective risk dilemmas) using fuzzy linguistic rules. We will first study evolutionary game theory models for exploring climate change policies and decisions to enhance cooperation between the policy players. Using computational agent-based simulations, we will build a framework where we incorporate and extend evolutionary game models with players' emotions in the game dynamics. These emotions, modeled by fuzzy linguistic rules, are a way for players to reconsider their strategies when playing the game. Results show how these rules representing emotions can better control defection in the collective-risk dilemmas while modeling a more realistic way of dealing with players' features.