Models used in DEXi Suite are prevalently qualitative. They are characterized by:
using qualitative (symbolic) tree-structured attributes, whose scales are discrete and typically consist of words rather than numbers,
employing aggregation functions that are represented by (tables of) decision rules rather that numerical formulae.
Here, the word “qualitative” is used for contrast with more traditional “quantitative” decision models, which are characterized by:
using continuous numerical attributes, which typically represent the decision-maker’s preferences, and
using numerical aggregation functions, such as the weighted sum.
In DEXi Suite, numerical attributes are supported to a limited extent and typically constitute just a fraction of DEX models. Numerical attributes can appear only as input attributes and are immediately mapped to some quantitative attribute using the corresponding discretization function.
Generally, a DEX model consists of:
attributes, structured in a tree,
qualitative and continuous scales associated with each attribute,
aggregation and discretization functions associated with aggregate attributes,
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