Preprocessing Argumentation Frameworks via Replacement Patterns

Wolfgang Dvořák, Matti Juhani Järvisalo, Thomas Linsbichler, Andreas Johannes Alexand Niskanen, Stefan Woltran

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKonferensbidragVetenskapligPeer review

Sammanfattning

A fast-growing research direction in the study of formal argumentation is the development of practical systems for central reasoning problems underlying argumentation. In particular, numerous systems for abstract argumentation frameworks (AF solvers) are available today, covering several argumentation semantics and reasoning tasks. Instead of proposing another algorithmic approach for AF solving, we introduce in this paper distinct AF preprocessing techniques as a solver-independent approach to obtaining performance improvements of AF solvers. We establish a formal framework of replacement patterns to perform local simplifications that are faithful with respect to standard semantics for AFs. Moreover, we provide a collection of concrete replacement patterns. Towards potential applicability, we employ the patterns in a preliminary empirical evaluation of their influence on AF solver performance.

Originalspråkengelska
Titel på värdpublikationLogics in Artificial Intelligence, JELIA 2019
RedaktörerFrancesco Calimeri, Nicola Leone, Marco Manna
Antal sidor17
Volym11468
FörlagSpringer
Utgivningsdatum2019
Sidor116-132
ISBN (tryckt)978-3-030-19569-4
ISBN (elektroniskt)978-3-030-19570-0
DOI
StatusPublicerad - 2019
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangEuropean Conference on Logics in Artificial Intelligence - Rende, Italien
Varaktighet: 7 maj 201911 maj 2019
Konferensnummer: 16
https://jelia2019.mat.unical.it/

Publikationsserier

NamnLecture Notes in Artificial Intelligence
FörlagSPRINGER INTERNATIONAL PUBLISHING AG
Volym11468
ISSN (tryckt)0302-9743

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