IJCAI 2024poster2 citations

Quantitative Claim-Centric Reasoning in Logic-Based Argumentation

Markus Hecher, Yasir Mahmood, Arne Meier, Johannes Schmidt

Abstract

Argumentation is a well-established formalism for nonmonotonic reasoning, with popular frameworks being Dung’s abstract argumentation (AFs) or logic-based argumentation (Besnard-Hunter’s framework). Structurally, a set of formulas forms support for a claim if it is consistent, subset-minimal, and implies the claim. Then, an argument comprises support and a claim. We observe that the computational task (ARG) of asking for support of a claim in a knowledge base is “brave”, since many claims with a single support are accepted. As a result, ARG falls short when it comes to the question of confidence in a claim, or claim strength. In this paper, we propose a concept for measuring the (acceptance) strength of claims, based on counting supports for a claim. Further, we settle classical and structural complexity of counting arguments favoring a given claim in propositional knowledge bases (KBs). We introduce quantitative reasoning to measure the strength of claims in a KB and to determine the relevance strength of a formula for a claim.

Knowledge Representation and Reasoning: KRR: ArgumentationKnowledge Representation and Reasoning: KRR: Computational complexity of reasoning
BibTeX
@inproceedings{ijcai2024p377,
  title     = {Quantitative Claim-Centric Reasoning in Logic-Based Argumentation},
  author    = {Hecher, Markus and Mahmood, Yasir and Meier, Arne and Schmidt, Johannes},
  booktitle = {Proceedings of the Thirty-Third International Joint Conference on
               Artificial Intelligence, {IJCAI-24}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Kate Larson},
  pages     = {3404--3412},
  year      = {2024},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2024/377},
  url       = {https://doi.org/10.24963/ijcai.2024/377},
}
Quantitative Claim-Centric Reasoning in Logic-Based Argumentation · IJCAI 2024