Stable model semantics for probabilistic deductive databases

Raymond Ng, V. S. Subrahmanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations


In this paper we study the uses and the semantics of non-monotonic negation in proba,- bilistie deductive databases. Based on the stable model semantics for classical logic programming, we examine two notions of stability. The first one is stable probabilistie models which are straightforward extensions of the classical stable models. But we prove that this notion may be too weak in our probabilistie framework. Then we introduce the second notion: stable families of probabilistie models. We show that this notion is much stronger than the first one, and we demonstrate how this stable family semantics can handle default reasoning appropriately in the context of probabilistic deduction.

Original languageEnglish (US)
Title of host publicationMethodologies for Intelligent Systems - 6th International Symposium, ISMIS 1991, Proceedings
EditorsZbigniew W. Ras, Maria Zemankova
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783540545637
StatePublished - 1991
Externally publishedYes
Event6th International Symposium on Methodologies for Intelligent Systems, ISMIS 1991 - Charlotte , United States
Duration: Oct 16 1991Oct 19 1991

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume542 LNAI Part F2
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other6th International Symposium on Methodologies for Intelligent Systems, ISMIS 1991
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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