Computing Preferred Answer Sets in Answer Set Programming

Abstract

Prioritized logic programs (PLPs) have a mechanism of representing priority knowledge in logic programs. The declarative semantics of a PLP is given as preferred answer sets which are used for representing nonmonotonic reasoning as well as preference abduction. From the computational viewpoint, however, its implementation issues have little been studied and no sound procedure is known for computing preferred answer sets of PLPs. In this paper, we present a sound and complete procedure to compute all preferred answer sets of a PLP in answer set programming. The procedure is based on a program transformation from a PLP to a logic program and is realized on top of any procedure for answer set programming. The proposed technique also extends PLPs to handle dynamic preference and we address its application to legal reasoning.