Learning Preferences in Prioritized Qualitative Choice Logic

Prioritized Qualitative Choice Logic (PQCL) is obtained from the propositional logic by adding a new logical connective, called ordered disjunction ( $\vec{\times}$ ) to express user preferences. Intuitively, if $x$ and $y$ are two outcomes then $x\vec{\times}y$ means: “if possible $x$ , but if $x$ is impossible then at least $y$ ”. In this paper, we propose a method for learning PQCL user's preferences. We evaluate the efficiency of the proposed method on real medical datasets.