Outlier detection for simple default theories

Fabrizio Angiulli, Rachel Ben-Eliyahu-Zohary, Luigi Palopoli

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

It was noted recently that the framework of default logics can be exploited for detecting outliers. Outliers are observations expressed by sets of literals that feature unexpected properties. These observations are not explicitly provided in input (as it happens with abduction) but, rather, they are hidden in the given knowledge base. Unfortunately, in the two related formalisms for specifying defaults - Reiter's default logic and extended disjunctive logic programs - the most general outlier detection problems turn out to lie at the third level of the polynomial hierarchy. In this note, we analyze the complexity of outlier detection for two very simple classes of default theories, namely NU and DNU, for which the entailment problem is solvable in polynomial time. We show that, for these classes, checking for the existence of an outlier is anyway intractable. This result contributes to further showing the inherent intractability of outlier detection in default reasoning.

Original languageEnglish
Pages (from-to)1247-1253
Number of pages7
JournalArtificial Intelligence
Volume174
Issue number15
DOIs
StatePublished - 1 Oct 2010

Keywords

  • Computational complexity
  • Data mining
  • Default logic
  • Disjunctive logic programming
  • Knowledge representation
  • Nonmonotonic reasoning
  • Outlier detection

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