# Argument Ranking with Categoriser Function

arXiv: https://arxiv.org/abs/1406.3877 · HTML: https://mlsanity.com/paper/1406.3877/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jun 2014.

## Built on by (most cited first, 6 of 6)

- [Analytical Solutions for the Inverse Problem within Gradual Semantics](https://mlsanity.com/paper/2203.01201/) (2022)
- [Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts](https://mlsanity.com/paper/2206.13959/) (2022)
- [Understanding Enthymemes in Argument Maps: Bridging Argument Mining and Logic-based Argumentation](https://mlsanity.com/paper/2408.08648/) (2024)
- [Some Options for Instantiation of Bipolar Argument Graphs with Deductive Arguments](https://mlsanity.com/paper/2308.04372/) (2023)
- [Identifying Reasons for Bias: An Argumentation-Based Approach](https://mlsanity.com/paper/2310.16506/) (2023)
- [Abstract Weighted Based Gradual Semantics in Argumentation Theory](https://mlsanity.com/paper/2401.11472/) (2024)

## Abstract (arXiv)

Recently, ranking-based semantics is proposed to rank-order arguments from the most acceptable to the weakest one(s), which provides a graded assessment to arguments. In general, the ranking on arguments is derived from the strength values of the arguments. Categoriser function is a common approach that assigns a strength value to a tree of arguments. When it encounters an argument system with cycles, then the categoriser strength is the solution of the non-linear equations. However, there is no detail about the existence and uniqueness of the solution, and how to find the solution (if exists). In this paper, we will cope with these issues via fixed point technique. In addition, we define the categoriser-based ranking semantics in light of categoriser strength, and investigate some general properties of it. Finally, the semantics is shown to satisfy some of the axioms that a ranking-based semantics should satisfy.