A Judgment Set Similarity Measure Based on Prime Implicants

Distances and scores are widely used to measure similarity between collections of information, such as preference profiles, belief sets, judgment sets, argument labelings, etc. Defining a function that quantifies the similarity between information sets of logically interrelated information is nontrivial, as witnessed by the shortage of such quantifiers in the literature. We propose a similarity measure for judgment sets that is "sensitive" to logic dependencies among the judgments.