Summary of An Extension-based Argument-ranking Semantics: Social Rankings in Abstract Argumentation Long Version, by Lars Bengel et al.
An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation Long Version
by Lars Bengel, Giovanni Buraglio, Jan Maly, Kenneth Skiba
First submitted to arxiv on: 18 Dec 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 This paper introduces a new family of argument-ranking semantics, refining classification into skeptically accepted, credulously accepted, and rejected arguments. Building on recent social ranking functions developed to rank individuals in groups, it provides necessary and sufficient conditions for these functions to give rise to an argument-ranking semantics satisfying the desired refinement property. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to understand how we accept or reject arguments. It uses ideas from social science to create a system that ranks arguments based on their strength. The goal is to make this system more accurate by providing specific rules for when an argument should be accepted, rejected, or somewhere in between. |
Keywords
» Artificial intelligence » Classification » Semantics
