@inproceedings{55655,
  abstract     = {{<jats:p>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.</jats:p>}},
  author       = {{Hecher, Markus and Mahmood, Yasir and Meier, Arne and Schmidt, Johannes}},
  booktitle    = {{Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence}},
  publisher    = {{International Joint Conferences on Artificial Intelligence Organization}},
  title        = {{{Quantitative Claim-Centric Reasoning in Logic-Based Argumentation}}},
  doi          = {{10.24963/ijcai.2024/377}},
  year         = {{2024}},
}