Gradual Semantics for Weighted Bipolar SETAFs

Bruno Yun, Srdjan Vesic* (Corresponding Author)

*Corresponding author for this work

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

7 Citations (Scopus)
4 Downloads (Pure)

Abstract

Gradual semantics are now well-studied in the computational argumentation literature. In this paper, we argue that gradual semantics that can handle both bipolarity (e.g. attacks and supports) and sets of attacking arguments (i.e. several arguments together attacking an argument) might be useful in some contexts. We define the formal framework and properties for such semantics. We proceed by adapting, studying and implementing three well-known semantics from the bipolar
gradual literature to this new framework.
Original languageEnglish
Title of host publicationSymbolic and Quantitative Approaches to Reasoning with Uncertainty 16th European Conference, ECSQARU 2021, Prague, Czech Republic, September 21–24, 2021, Proceedings
EditorsJiřina Vejnarová, Nic Wilson
Place of PublicationSwitzerland
PublisherSpringer
Pages201-214
Number of pages14
Edition1
ISBN (Electronic)978-3-030-86772-0
ISBN (Print)978-3-030-86771-3
DOIs
Publication statusPublished - 19 Sept 2021
EventSixteenth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2021) - Prague, Czech Republic
Duration: 21 Sept 202124 Sept 2021
Conference number: 16th
https://ecsqaru.utia.cas.cz/

Publication series

NameLecture Notes in Artificial Intelligence
PublisherSpringer
Volume12897
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceSixteenth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2021)
Abbreviated titleECSQARU 2021
Country/TerritoryCzech Republic
CityPrague
Period21/09/2124/09/21
Internet address

Bibliographical note

Srdjan Vesic was supported by “Responsible AI” ANR Chair in Artificial Intelligence, https://ia-responsable.eu/.

Keywords

  • Argumentation
  • Gradual semantics

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