 The outcome of the merging operator clearly depends on the chosen distance functions d and D. Among the first proposals (Lin and Mendelzon 1999; Revesz 1993) it was to adopt the Hamming distance (defined below) for d and the sum or the max for D (denoted respectively \(D_{\Sigma}\) and  \(D_{\mymax}\)).[3]  When D is the sum, the global distance is obtained by summing the individual ones. The corresponding merging operator is a majority operator and is called minisum as it will select those interpretations that minimize the sum. The merging operator that uses \(D_{\mymax}\) is known as minimax and outputs the judgment set that minimizes the maximal distance to the individual bases (Brams et al. 2007b). Intuitively, minimax aims at minimizing the disagreement with the most dissatisfied individual. Two opposite outcomes may be selected when \(D_{\Sigma}\) or \(D_{\mymax}\) is used (Brams et al. 2007b; Eckert and Klamler 2007).