A multidimensional spatial model for preference representation in multi-criteria decision aiding

Abstract

In this work we propose to use a multidimensional spatial model to represent preferences of multiple decision makers in multi-criteria decision aiding. The decision makers are represented in a shared space with the alternatives so that their positions are consistent with the preferences that they express on pairs of alternatives. We show how the parameters of this preference model can be learnt from holistic preference judgements, and discuss its various consequences and properties