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  • 标题:Aggregation in Value-Based Argumentation Frameworks
  • 本地全文:下载
  • 作者:Grzegorz Lisowski ; Sylvie Doutre ; Umberto Grandi
  • 期刊名称:Electronic Proceedings in Theoretical Computer Science
  • 电子版ISSN:2075-2180
  • 出版年度:2019
  • 卷号:297
  • 页码:313-331
  • DOI:10.4204/EPTCS.297.20
  • 语种:English
  • 出版社:Open Publishing Association
  • 摘要:Value-based argumentation enhances a classical abstract argumentation graph - in which arguments are modelled as nodes connected by directed arrows called attacks - with labels on arguments, called values, and an ordering on values, called audience, to provide a more fine-grained justification of the attack relation. With more than one agent facing such an argumentation problem, agents may differ in their ranking of values. When needing to reach a collective view, such agents face a dilemma between two equally justifiable approaches: aggregating their views at the level of values, or aggregating their attack relations, remaining therefore at the level of the graphs. We explore the strengths and limitations of both approaches, employing techniques from preference aggregation and graph aggregation, and propose a third possibility aggregating rankings extracted from given attack relations.
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