Extending NetLogo with Interval Type-2 Fuzzy Inference Systems

The use of computational intelligence in a Multi-Agent System (MAS) can aid the process of modelling complex social phenomena. Fuzzy Inference Systems (FIS) have been broadly used in control systems on engineering applications, but this also in Social Simulation could be very useful due the possibility to represent non-linear systems. In Type-2 Fuzzy Logic, uncertainty was introduced on the model enriching the capability of description in complex decision-making systems. In this paper, we introduce an Interval Type-2 Fuzzy Inference System extension for Netlogo, which is a very used computational modelling tool. With this extension, we aim to implement complex decision making systems in MAS and Social Simulation using Type-2 Fuzzy Logic.