Fuzzy labelling semantics for quantitative argumentation

被引:0
|
作者
Wang, Zongshun [1 ]
Shen, Yuping [1 ]
机构
[1] Sun Yat Sen Univ, Inst Log & Cognit, Dept Philosophy, Guangzhou 510275, Peoples R China
关键词
abstract argumentation; quantitative argumentation; fuzzy labelling semantics; evaluation of strength; ABSTRACT ARGUMENTATION;
D O I
10.1093/logcom/exaf009
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
argumentation is a well-studied model for evaluating arguments. Recently, evaluating argument strength in quantitative argumentation has received increasing attention, in which arguments are evaluated through acceptability degree. However, argument strength solely defined on acceptability degree appears not sufficient in practical applications. In this paper, we provide a novel quantitative method called fuzzy labelling for fuzzy argumentation systems, in which a triple of acceptability, rejectability and undecidability degrees is used to evaluate argument strength. Such a setting sheds new light on defining argument strength and provides a deeper understanding of the status of arguments. Specifically, we investigate the postulates of fuzzy labelling, which present the rationality requirements for semantics concerning the acceptability, rejectability and undecidability degrees. We then propose a class of fuzzy labelling semantics conforming to the above postulates and investigate the properties. Finally, we demonstrate that fuzzy labelling semantics can be considered both a conservative generalization of classical labelling semantics and a labelling version of fuzzy extension semantics.
引用
收藏
页数:30
相关论文
共 50 条
  • [21] A labelling framework for probabilistic argumentation
    Riveret, Regis
    Baroni, Pietro
    Gao, Yang
    Governatori, Guido
    Rotolo, Antonino
    Sartor, Giovanni
    ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE, 2018, 83 (01) : 21 - 71
  • [22] Characterization of Argumentation Semantics in Terms of the MMr Semantics
    Osorio, Mauricio
    Luis Carballido, Jose
    Zepeda, Claudia
    Cruz, Zenaida
    ADVANCES IN ARTIFICIAL INTELLIGENCE, PT I, 2011, 7094 : 16 - +
  • [23] Handling ignorance in argumentation: Semantics of partial argumentation frameworks
    Cayrol, C.
    Devred, C.
    Lagasquie-Schiex, M. C.
    SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY, PROCEEDINGS, 2007, 4724 : 259 - +
  • [24] Forbidden Sets in Argumentation Semantics
    Dunne, Paul E.
    COMPUTATIONAL MODELS OF ARGUMENT, 2016, 287 : 275 - 286
  • [25] DECOMPOSING SEMANTICS IN ABSTRACT ARGUMENTATION
    Baroni, Pietro
    Cerutti, Federico
    Giacomin, Massimiliano
    JOURNAL OF APPLIED LOGICS-IFCOLOG JOURNAL OF LOGICS AND THEIR APPLICATIONS, 2023, 10 (03):
  • [26] Comparing the Expressiveness of Argumentation Semantics
    Dvorak, Wolfgang
    Spanring, Christof
    COMPUTATIONAL MODELS OF ARGUMENT, 2012, 245 : 261 - +
  • [27] Serialisable Semantics for Abstract Argumentation
    Bengel, Lars
    Thimm, Matthias
    COMPUTATIONAL MODELS OF ARGUMENT, COMMA 2022, 2022, 353 : 80 - 91
  • [28] Prudent semantics for argumentation frameworks
    Coste-Marquis, S
    Devred, C
    Marquis, P
    ICTAI 2005: 17TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2005, : 568 - 572
  • [29] A Replication Study of Semantics in Argumentation
    Amgoud, Leila
    PROCEEDINGS OF THE TWENTY-EIGHTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2019, : 6260 - 6266
  • [30] On the Functional Completeness of Argumentation Semantics
    Giacomin, Massimiliano
    Linsbichler, Thomas
    Woltran, Stefan
    FIFTEENTH INTERNATIONAL CONFERENCE ON THE PRINCIPLES OF KNOWLEDGE REPRESENTATION AND REASONING, 2016, : 43 - 52