Axiom Pinpointing in General Tableaux

Axiom pinpointing has been introduced in description logics (DLs) to help the user to understand the reasons why consequences hold and to remove unwanted consequences by computing minimal (maximal) subsets of the knowledge base that have (do not have) the consequence in question. The pinpointing algorithms described in the DL literature are obtained as extensions of the standard tableau-based reasoning algorithms for computing consequences from DL knowledge bases. Although these extensions are based on similar ideas, they are all introduced for a particular tableau-based algorithm for a particular DL. The purpose of this paper is to develop a general approach for extending a tableau-based algorithm to a pinpointing algorithm. This approach is based on a general definition of “tableaux algorithms,” which captures many of the known tableau-based algorithms employed in DLs, but also other kinds of reasoning procedures.

• Type: Conference
• Year: 2007
• Where: TABLEAUX
• Authors: Franz Baader, Rafael Peñaloza
• Keywords: Artificial Intelligence, Pinpointing Algorithm, Tableau-based Algorithms, Tableau-based Reasoning Algorithms, TABLEAUX 2007