Towards context sensitive defeasible rules

Armin Hezart*, Abhaya Nayak, Mehmet Orgun

*Corresponding author for this work

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

Abstract

Defeasible argumentation systems are used to model commonsense and defeasible reasoning. Current argumentation systems assume that an argument that appears to be justified also satisfies our expectation in relation to the correct outcome, and, vice versa. In this paper we present an alternative representation of defeasible rules, tailored for argumentation based defeasible reasoning, that is free of such an assumption. We provide a mapping between our argumentation system and Dung's abstract argumentation theory to show its efficacy.

Original languageEnglish
Title of host publicationComputational logic in multi-agent systems
Subtitle of host publication8th international workshop, CLIMA VIII, Porto, Portugal, September 2007; revised selected and invited papers
EditorsFariba Sadri, Ken Satoh
Place of PublicationBerlin
PublisherSpringer, Springer Nature
Pages193-213
Number of pages21
ISBN (Print)3540888322, 9783540888321
DOIs
Publication statusPublished - 2008
Event8th International Workshop on Computational Logic in Multi-Agent Systems, CLIMA VIII - Porto, Portugal
Duration: 10 Sep 200711 Sep 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5056 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th International Workshop on Computational Logic in Multi-Agent Systems, CLIMA VIII
CountryPortugal
CityPorto
Period10/09/0711/09/07

    Fingerprint

Cite this

Hezart, A., Nayak, A., & Orgun, M. (2008). Towards context sensitive defeasible rules. In F. Sadri, & K. Satoh (Eds.), Computational logic in multi-agent systems: 8th international workshop, CLIMA VIII, Porto, Portugal, September 2007; revised selected and invited papers (pp. 193-213). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5056 LNAI). Berlin: Springer, Springer Nature. https://doi.org/10.1007/978-3-540-88833-8_11