Representing and Manipulating Large Sequences of Argumentation Labellings

Odinaldo Rodrigues

doi:10.1145/3555776.3577756

Representing and Manipulating Large Sequences of Argumentation Labellings

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

This paper proposes a canonical ordering of arguments within abstract argumentation labellings and two new types of efficient representations of these labellings for use in applications involving the computation of argumentation semantics. The space requirements of the representations are analysed, benchmarked on a class of hard enumeration problems taken from the International Competition on Computational Models of Argumentation (ICCMA), and compared for efficiency. We found that they both offer significant reductions of the memory representation requirements of large labellings, sometimes of up to 75%. We argue that the new way of looking at labellings provided by one of the representations, i.e., by considering repetitions of segment assignments within labellings, paves the way for investigations of new applications in argumentation theory.

Original language	English
Title of host publication	The 38th ACM/SIGAPP Symposium on Applied Computing (SAC’23)
Place of Publication	New York
Number of pages	8
DOIs	https://doi.org/10.1145/3555776.3577756
Publication status	Accepted/In press - 22 Dec 2022

Keywords

argumentation theory
computation models of argumentation
representation of labellings

Access to Document

10.1145/3555776.3577756Licence: Other

Cite this

@inbook{fa69f212f3ff444891b2ebf9351dc9b3,

title = "Representing and Manipulating Large Sequences of Argumentation Labellings",

abstract = "This paper proposes a canonical ordering of arguments within abstract argumentation labellings and two new types of efficient representations of these labellings for use in applications involving the computation of argumentation semantics. The space requirements of the representations are analysed, benchmarked on a class of hard enumeration problems taken from the International Competition on Computational Models of Argumentation (ICCMA), and compared for efficiency. We found that they both offer significant reductions of the memory representation requirements of large labellings, sometimes of up to 75%. We argue that the new way of looking at labellings provided by one of the representations, i.e., by considering repetitions of segment assignments within labellings, paves the way for investigations of new applications in argumentation theory.",

keywords = "argumentation theory, computation models of argumentation, representation of labellings",

author = "Odinaldo Rodrigues",

year = "2022",

month = dec,

day = "22",

doi = "10.1145/3555776.3577756",

language = "English",

booktitle = "The 38th ACM/SIGAPP Symposium on Applied Computing (SAC{\textquoteright}23)",

}

TY - CHAP

T1 - Representing and Manipulating Large Sequences of Argumentation Labellings

AU - Rodrigues, Odinaldo

PY - 2022/12/22

Y1 - 2022/12/22

N2 - This paper proposes a canonical ordering of arguments within abstract argumentation labellings and two new types of efficient representations of these labellings for use in applications involving the computation of argumentation semantics. The space requirements of the representations are analysed, benchmarked on a class of hard enumeration problems taken from the International Competition on Computational Models of Argumentation (ICCMA), and compared for efficiency. We found that they both offer significant reductions of the memory representation requirements of large labellings, sometimes of up to 75%. We argue that the new way of looking at labellings provided by one of the representations, i.e., by considering repetitions of segment assignments within labellings, paves the way for investigations of new applications in argumentation theory.

AB - This paper proposes a canonical ordering of arguments within abstract argumentation labellings and two new types of efficient representations of these labellings for use in applications involving the computation of argumentation semantics. The space requirements of the representations are analysed, benchmarked on a class of hard enumeration problems taken from the International Competition on Computational Models of Argumentation (ICCMA), and compared for efficiency. We found that they both offer significant reductions of the memory representation requirements of large labellings, sometimes of up to 75%. We argue that the new way of looking at labellings provided by one of the representations, i.e., by considering repetitions of segment assignments within labellings, paves the way for investigations of new applications in argumentation theory.

KW - argumentation theory

KW - computation models of argumentation

KW - representation of labellings

U2 - 10.1145/3555776.3577756

DO - 10.1145/3555776.3577756

M3 - Conference paper

BT - The 38th ACM/SIGAPP Symposium on Applied Computing (SAC’23)

CY - New York

ER -

Representing and Manipulating Large Sequences of Argumentation Labellings

Abstract

Keywords

Access to Document

Other files and links

Embargoed Document

Fingerprint

Cite this