Open-Mindedness of Gradual Argumentation Semantics

Autor(en): Potyka, N.
Herausgeber: Ben Amor, N.
Quost, B.
Theobald, M.
Stichwörter: Argumentation semantics; Decision support systems, Argumentation frameworks; Decision supports; Gradual argumentation; Semantical properties; Social media analysis; Strength values; Weighted argumentation; Weighted argumentation, Semantics
Erscheinungsdatum: 2019
Herausgeber: Springer
Enthalten in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band: 11940 LNAI
Startseite: 236
Seitenende: 249
Zusammenfassung: 
Gradual argumentation frameworks allow modeling arguments and their relationships and have been applied to problems like decision support and social media analysis. Semantics assign strength values to arguments based on an initial belief and their relationships. The final assignment should usually satisfy some common-sense properties. One property that may currently be missing in the literature is Open-Mindedness. Intuitively, Open-Mindedness is the ability to move away from the initial belief in an argument if sufficient evidence against this belief is given by other arguments. We generalize and refine a previously introduced notion of Open-Mindedness and use this definition to analyze nine gradual argumentation approaches from the literature. © Springer Nature Switzerland AG 2019.
Beschreibung: 
Conference of 13th International Conference on Scalable Uncertainty Management, SUM 2019 ; Conference Date: 16 December 2019 Through 18 December 2019; Conference Code:235739
ISBN: 9783030355135
ISSN: 03029743
DOI: 10.1007/978-3-030-35514-2_18
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078503364&doi=10.1007%2f978-3-030-35514-2_18&partnerID=40&md5=2086f150bbd985a27d0e4a927eed6f3d

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