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Recently, there has been much research into modelling of uncertainty in humanperception through Fuzzy Sets (FSs). Most of this research has focused onallowing respondents to express their (intra) uncertainty using intervals.Here, depending on the technique used and types of uncertainties being modelleddifferent types of FSs can be obtained (e.g., Type-1, Interval Type-2, GeneralType-2). Arguably, one of the most flexible techniques is the IntervalAgreement Approach (IAA) as it allows to model the perception of allrespondents without making assumptions such as outlier removal or predefinedmembership function types (e.g. Gaussian). A key aspect in the analysis ofinterval-valued data and indeed, IAA based agreement models of said data, is todetermine the position and strengths of agreement across all thesources/participants. While previously, the Agreement Ratio was proposed tomeasure the strength of agreement in fuzzy set based models of interval data,said measure has only been applicable to type-1 fuzzy sets. In this paper, weextend the Agreement Ratio to capture the degree of inter-group agreementmodelled by a General Type-2 Fuzzy Set when using the IAA. This measure relieson using a similarity measure to quantitatively express the relation betweenthe different levels of agreement in a given FS. Synthetic examples areprovided in order to demonstrate both behaviour and calculation of the measure.Finally, an application to real-world data is provided in order to show thepotential of this measure to assess the divergence of opinions for ambiguousconcepts when heterogeneous groups of participants are involved.

Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets