A General Setting for Gradual Semantics Dealing with Similarity

Abstract

The paper discusses theoretical foundations that describe principles and processes involved in defining semantics that deal with similarity between arguments. Such semantics compute the strength of an argument on the basis of the strengths of its attackers, similarities between those attackers, and an initial weight ascribed to the argument. We define a semantics by three functions: an adjustment function that updates the strengths of attackers on the basis of their similarities, an aggregation function that computes the strength of the group of attackers, and an influence function that evaluates the impact of the group on the argument's initial weight. We propose intuitive constraints for the three functions and key rationality principles for semantics, and show how the former lead to the satisfaction of the latter. Then, we propose a broad family of semantics whose instances satisfy the principles. Finally, we analyse the existing adjustment functions and show that they violate some properties, then we propose novel ones and use them for generalizing h-Categorizer.

Bilateral Gradual Semantics for Weighted Argumentation

“…In recent years, the gradual semantics has emerged as a prominent approach for evaluating arguments (Amgoud et al 2017;Amgoud and Doder 2018;Amgoud and David 2021;Amgoud, Doder, and Vesic 2022;Baroni, Rago, and Toni 2018;Oren et al 2022;Prakken 2021). This method provides a fine-grained evaluation scheme which introduces the notion of acceptability degree to describe argument strength.…”

Similarity Measures Based on Compiled Arguments

“…They introduced a set of principles that a reasonable similarity measure should satisfy, and provided several measures that satisfy them. In [12,13,14] several extensions of h-Categorizer that take into account similarities between arguments have been proposed.…”