Logic programming and uncertainty

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

2 Scopus citations


In recent years Logic programming based languages and features-such as rules and non-monotonic constructs-have become important in various knowledge representation paradigms. While the early logic programming languages, such as Horn logic programs and Prolog did not focus on expressing and reasoning with uncertainty, in recent years logic programming languages have been developed that can express both logical and quantitative uncertainty. In this paper we give an overview of such languages and the kind of uncertainty they can express and reason with. Among those, we slightly elaborate on the language P-log that not only accommodates probabilistic reasoning, but also respects causality and distinguishes observational and action updates.

Original languageEnglish (US)
Title of host publicationScalable Uncertainty Management - 5th International Conference, SUM 2011, Proceedings
Number of pages16
StatePublished - 2011
Event5th International Conference on Scalable Uncertainty Management, SUM 2011 - Dayton, OH, United States
Duration: Oct 10 2011Oct 13 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6929 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th International Conference on Scalable Uncertainty Management, SUM 2011
Country/TerritoryUnited States
CityDayton, OH

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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