A General Setting for Gradual Semantics Dealing with Similarity

Authors

  • Leila Amgoud IRIT - CNRS - ANITI - Toulouse University
  • Victor David IRIT - CNRS - Toulouse University

Keywords:

Argumentation

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.

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Published

2021-05-18

How to Cite

Amgoud, L., & David, V. (2021). A General Setting for Gradual Semantics Dealing with Similarity. Proceedings of the AAAI Conference on Artificial Intelligence, 35(7), 6185-6192. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16769

Issue

Section

AAAI Technical Track on Knowledge Representation and Reasoning