On aggregation operators for ordinal qualitative information

In many fuzzy systems applications, values to be aggregated are of a qualit ative nature. In that case, if one wants to compute some type of average, t he most common procedure is to perform a numerical interpretation of the va lues, and then apply one of the well-known (the most suitable) numerical ag gregation operators. However, if one wants to stick to a purely qualitative setting, choices are reduced to either weighted versions of max-min combin ations or to a few existing proposals of qualitative versions of OWA operat ors. In this paper, we explore the feasibility of defining a qualitative co unterpart of the weighted mean operator without having to use necessarily a ny numerical interpretation of the values. We propose a method to average q ualitative values, belonging to a (finite) ordinal scale, weighted with nat ural numbers, and based on the use of finite t-norms and t-conorms defined on the scale of values. Extensions of the method for other OWA-like :Ind Ch oquet integral-type aggregations are also considered.