Abstract
The stable model semantics of disjunctive logic programs is based on minimal models which assign atoms false by default. While this feature is highly useful and leads to concise problem encodings, it occasionally makes knowledge representation with disjunctive rules difficult. Lifschitz’ parallel circumscription provides a remedy by introducing atoms that are allowed to vary or to have fixed values while others are falsified. Prioritized circumscription further refines this setting in terms of priority classes for atoms being falsified. In this paper, we present a linear and faithful transformation to embed prioritized circumscription into disjunctive logic programming in a systematic fashion. The implementation of the method enables the use of disjunctive solvers for computing prioritized circumscription. The results of an experimental evaluation indicate that the method proposed herein compares favorably with other existing implementations.
This research has been partially funded by the Academy of Finland under project #122399. A preliminary version of this work appeared in [1]
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Oikarinen, E., Janhunen, T. (2008). Implementing Prioritized Circumscription by Computing Disjunctive Stable Models. In: Dochev, D., Pistore, M., Traverso, P. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2008. Lecture Notes in Computer Science(), vol 5253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85776-1_15
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