Qualitative Decision Making and Answer Set Programming Extended Abstract

In a recent paper [BBL02] a propositional logic called Qualitative Choice Logic ( ) was introduced. The logic contains a new connective representing ordered disjunction. Intuitively, stands for: if possible , but if is impossible then (at least) . This connective allows context dependent preferences to be represented in a simple and elegant fashion. In this paper we show how to combine ideas underlying with logic programming and how to use the resulting framework for qualitative decision making. The semantical framework in which the investigation will be carried out is that of answer set semantics [GL91]. Intuitively, answer sets are sets of literals describing plausible states of the world given the knowledge represented in a program. There are several interesting AI applications of answer set programming, for instance in planning and configuration. One of the reasons for this success is the availability of highly efficient systems for computing answer sets like smodels [NS97] and dlv [ELM 98].