# An Approach to Characterize Graded Entailment of Arguments through a Label-based Framework

## TL;DR

This paper proposes a label-based framework to characterize graded entailment of arguments, incorporating various qualities like strength, trust, and relevance to better model human-like reasoning.

## Contribution

It introduces a novel framework that extends classical argumentation by integrating multiple qualitative measures for a more nuanced acceptability assessment.

## Key findings

- Framework effectively models graded argument acceptability
- Incorporates multiple qualities like trust and relevance
- Enhances human-like reasoning in argumentation systems

## Abstract

Argumentation theory is a powerful paradigm that formalizes a type of commonsense reasoning that aims to simulate the human ability to resolve a specific problem in an intelligent manner. A classical argumentation process takes into account only the properties related to the intrinsic logical soundness of an argument in order to determine its acceptability status. However, these properties are not always the only ones that matter to establish the argument's acceptability---there exist other qualities, such as strength, weight, social votes, trust degree, relevance level, and certainty degree, among others.