Agent-based models are useful to study emergent behaviour in social systems. In general, existing agent models tend to be quite simple, but there are social problems that require the consideration of some aspects with uncertainty as human thinking does. Those characteristics can be addressed by using fuzzy sets theory in the specification of the attributes that describe agents representing individuals, and in the functions that model the evolution of individual change of mind, the relationships among individuals in a social network, the inheritance, and the similarity between individuals. This paper discusses the fuzzification of agent-based models and analyses experimentation results for a specific case of the study of the evolution of human values in a society.
['Samer Hassan', 'Luis Garmendia', 'Juan Pavón']
Introducing uncertainty into social simulation: using fuzzy logic for agent-based modelling