Fuzzy Labeling Semantics for Quantitative Argumentation
Zongshun Wang, Yuping Shen

TL;DR
This paper introduces fuzzy labeling, a novel quantitative approach for evaluating argument strength in abstract argumentation systems using acceptability, rejectability, and undecidability degrees, enhancing the understanding of argument status.
Contribution
It proposes a new fuzzy labeling semantics that incorporates three degrees for argument evaluation, addressing limitations of traditional acceptability measures.
Findings
Fuzzy labeling semantics conform to rationality postulates.
The new semantics relate to existing argumentation frameworks.
Provides a deeper understanding of argument strength evaluation.
Abstract
Evaluating argument strength in quantitative argumentation systems has received increasing attention in the field of abstract argumentation. The concept of acceptability degree is widely adopted in gradual semantics, however, it may not be sufficient in many practical applications. In this paper, we provide a novel quantitative method called fuzzy labeling 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. More specifically, we investigate the postulates of fuzzy labeling, which present the rationality requirements for semantics concerning the acceptability, rejectability, and undecidability degrees. We then propose a class of fuzzy labeling semantics conforming to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMulti-Agent Systems and Negotiation · Software Engineering Research · Business Process Modeling and Analysis
