A General Setting for Gradual Semantics Dealing with Similarity - Intelligence Artificielle Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

A General Setting for Gradual Semantics Dealing with Similarity

Résumé

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.
Fichier principal
Vignette du fichier
707.AmgoudL.pdf (329.01 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03141729 , version 1 (15-02-2021)

Identifiants

  • HAL Id : hal-03141729 , version 1

Citer

Leila Amgoud, Victor David. A General Setting for Gradual Semantics Dealing with Similarity. 35th AAAI Conference en Artificial Intelligence (AAAI 2021), AAAI : Association for the Advancement of Artificial Intelligence, Feb 2021, Virtual Conference, United States. pp.6185-6192. ⟨hal-03141729⟩
123 Consultations
106 Téléchargements

Partager

Gmail Facebook X LinkedIn More