Title: Introducing uncertainty into social simulation: using fuzzy logic for agent-based modelling
Authors: Samer Hassan, Luis Garmendia, Juan Pavon
Addresses: Facultad de Informatica, Universidad Complutense Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain. ' Facultad de Informatica, Universidad Complutense Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain. ' Facultad de Informatica, Universidad Complutense Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain
Abstract: 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.
Keywords: agent-based social simulation; ABSS; agent-based modelling; ABM; complexity; European Values Survey; EVS; fuzzy agents; fuzzy logic; fuzzification; multi-agent systems; MAS; reasoning-based intelligent systems; similarity; social networking; uncertainty; agent-based systems.
DOI: 10.1504/IJRIS.2010.034907
International Journal of Reasoning-based Intelligent Systems, 2010 Vol.2 No.2, pp.118 - 124
Published online: 30 Aug 2010 *
Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article