Quantitative Claim-Centric Reasoning in Logic-Based Argumentation

Quantitative Claim-Centric Reasoning in Logic-Based Argumentation

Markus Hecher, Yasir Mahmood, Arne Meier, Johannes Schmidt

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
Main Track. Pages 3404-3412. https://doi.org/10.24963/ijcai.2024/377

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.
Keywords:
Knowledge Representation and Reasoning: KRR: Argumentation
Knowledge Representation and Reasoning: KRR: Computational complexity of reasoning