An argument-based approach to using multiple ontologies

Elizabeth Black*, Anthony Hunter, Jeff Z. Pan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

24 Citations (Scopus)

Abstract

Logic-based argumentation offers an approach to querying and revising multiple ontologies that are inconsistent or incoherent. A common assumption for logic-based argumentation is that an argument is a pair Φ,α where Φ is a minimal subset of the knowledgebase such that Φ is consistent and Φ entails the claim α. Using dialogue games, agents (each with its own ontology) can exchange arguments and counterarguments concerning formulae of interest. In this paper, we present a novel framework for logic-based argumentation with ontological knowledge. As far as we know, this is the first proposal for argumentation with multiple ontologies via dialogues. It allows two agents to discuss the answer to queries concerning their knowledge (even if it is inconsistent) without one agent having to copy all of their ontology to the other, and without the other agent having to expend time and effort merging that ontology with theirs. Furthermore, it offers the potential for the agents to incrementally improve their knowledge based on the dialogue by checking how it differs from the other agent's.

Original languageEnglish
Title of host publicationScalable Uncertainty Management - Third International Conference, SUM 2009, Proceedings
EditorsLluís Godo, Andrea Pugliese
Pages68-79
Number of pages12
DOIs
Publication statusPublished - 4 Nov 2009
Event3rd International Conference on Scalable Uncertainty Management, SUM 2009 - Washington, DC, United States
Duration: 28 Sept 200930 Sept 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5785 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Scalable Uncertainty Management, SUM 2009
Country/TerritoryUnited States
CityWashington, DC
Period28/09/0930/09/09

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