Eliciting Rational Initial Weights in Gradual Argumentation

TL;DR

This paper introduces a new method for eliciting initial argument weights in weighted argumentation frameworks by using acceptability degree intervals and gradual semantics to improve accuracy and rationality.

Contribution

It presents an elicitation pipeline that refines acceptability intervals to determine initial weights, addressing challenges in user input and interpretation.

Findings

The pipeline effectively refines acceptability intervals.

It restores rationality when initial inputs are inconsistent.

It identifies possible initial weights for arguments.

Abstract

Many semantics for weighted argumentation frameworks assume that each argument is associated with an initial weight. However, eliciting these initial weights poses challenges: (1) accurately providing a specific numerical value is often difficult, and (2) individuals frequently confuse initial weights with acceptability degrees in the presence of other arguments. To address these issues, we propose an elicitation pipeline that allows one to specify acceptability degree intervals for each argument. By employing gradual semantics, we can refine these intervals when they are rational, restore rationality when they are not, and ultimately identify possible initial weights for each argument.