Abstract

Conflict detection is used in many scenarios ranging from interactive decision making to the diagnosis of potentially faulty hardware components or models. In these scenarios, the efficient identification of conflicts is crucial. Junker’s QuickXPlain is a divide-and-conquer based algorithm for the determination of preferred minimal conflicts. Motivated by the increasing size and complexity of knowledge bases, we propose a parallelization of the original algorithm that helps to significantly improve runtime performance especially in complex knowledge bases. In this paper, we introduce a parallelized version of QuickXPlain that is based on the idea of predicting and executing parallel consistency checks needed by QuickXPlain.