Belief revision in structured probabilistic argumentation

Paulo Shakarian, Gerardo I. Simari, Marcelo A. Falappa

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

9 Scopus citations


In real-world applications, knowledge bases consisting of all the information at hand for a specific domain, along with the current state of affairs, are bound to contain contradictory data coming from different sources, as well as data with varying degrees of uncertainty attached. Likewise, an important aspect of the effort associated with maintaining knowledge bases is deciding what information is no longer useful; pieces of information (such as intelligence reports) may be outdated, may come from sources that have recently been discovered to be of low quality, or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing the basic issues of handling contradictory and uncertain data. Then, to address the last issue, we focus on the study of non-prioritized belief revision operations over probabilistic PreDeLP programs. We propose a set of rationality postulates - based on well-known ones developed for classical knowledge bases - that characterize how such operations should behave, and study a class of operators along with theoretical relationships with the proposed postulates, including a representation theorem stating the equivalence between this class and the class of operators characterized by the postulates.

Original languageEnglish (US)
Title of host publicationFoundations of Information and Knowledge Systems - 8th International Symposium, FoIKS 2014, Proceedings
Number of pages20
StatePublished - 2014
Externally publishedYes
Event8th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2014 - Bordeaux, France
Duration: Mar 3 2014Mar 7 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8367 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other8th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2014

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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