Implementing Prioritized Logic Programming

Connict resolution is an important issue in knowledge representation and reasoning. A common idea of solving connicts in reasoning is to introduce priorities in the underlying reasoning mechanism. This paper describes an implementation of prioritized logic programs (PLPs) proposed by Zhang and Foo recently 4]. PLPs is a non-trivial extension of Gelfond and Lifschitz's extended logic programs 3] by associating preferences to the program, where answer sets provide a semantics of PLPs. As a central part of the implementation of PLPs, we present major algorithms of computing answer sets of PLPs. We show how answer sets of a PLP can be computed eeciently based on previous Niemell a and Simons' method of computing stable models of logic programs 2].