Computing Preferences in Abstract Argumentation

Quratul Ain Mahesar, Nir Oren, Wamberto W. Vasconcelos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)


We present an extension-based approach for computing preferences in an abstract argumentation system. Although numerous argumentation semantics have been developed previously for identifying acceptable sets of arguments from an argumentation framework, there is a lack of justification behind their acceptability based on implicit argument preferences. This paper presents a novel algorithm for exhaustively computing and enumerating all possible sets of preferences for a conflict-free set of arguments in an abstract argumentation framework. We prove the soundness and completeness of the algorithm. The research establishes that preferences are determined using an extension-based approach after the evaluation phase (acceptability of arguments) rather than stated beforehand. We also present some novel insights by comparing the computed preferences for the extensions.

Original languageEnglish
Title of host publicationPRIMA 2018: Principles and Practice of Multi-Agent Systems
Subtitle of host publication21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings
EditorsTim Miller, Nir Oren, Yuko Sakurai, Itsuki Noda, Bastin Tony Roy Savarimuthu, Tran Cao Son
PublisherSpringer, Cham
Number of pages16
VolumeLNCS/LNAI 11224
ISBN (Electronic)9783030030988
ISBN (Print)9783030030971
Publication statusPublished - 24 Oct 2018
Externally publishedYes
Event21st International Conference on Principles and Practice of Multi-Agent Systems - Tokyo, Japan
Duration: 29 Oct 20182 Nov 2018
Conference number: 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11224 LNCS/LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International Conference on Principles and Practice of Multi-Agent Systems
Abbreviated titlePRIMA 2018


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