Summary of Abstract Weighted Based Gradual Semantics in Argumentation Theory, by Assaf Libman et al.
Abstract Weighted Based Gradual Semantics in Argumentation Theory
by Assaf Libman, Nir Oren, Bruno Yun
First submitted to arxiv on: 21 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a new approach to argumentation theory, introducing “weighted gradual semantics” that assign an acceptability degree to each argument based on factors such as background evidence and interactions with other arguments. The authors identify four key problems in this area: reexamining the inverse problem, determining the injectivity of the mapping between argument weights and acceptability degrees, considering preferences rather than acceptability degrees, and analyzing the topology of the space of valid acceptability degrees. To address these challenges, the paper introduces a large family of weighted gradual semantics called abstract weighted-based gradual semantics, which generalize many existing semantics while maintaining desirable properties such as convergence to a unique fixed point. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to understand how arguments are accepted or rejected. It’s like a special kind of math that helps us figure out why people agree or disagree with each other. The authors want to know how to make this math work in different situations, and they propose a new approach called “weighted gradual semantics”. This approach is important because it can help us understand what makes an argument strong or weak, and how we can use that information to make better decisions. |
Keywords
» Artificial intelligence » Semantics
