A General Setting for Gradual Semantics Dealing with Similarity


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






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.




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. https://doi.org/10.1609/aaai.v35i7.16769



AAAI Technical Track on Knowledge Representation and Reasoning