Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
| Herausgeber/-innen | Kate Larson |
| Seiten | 3404-3412 |
| Seitenumfang | 9 |
| ISBN (elektronisch) | 9781956792041 |
| Publikationsstatus | Veröffentlicht - 2024 |
Publikationsreihe
| Name | IJCAI International Joint Conference on Artificial Intelligence |
|---|---|
| ISSN (Print) | 1045-0823 |
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 a 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.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024. Hrsg. / Kate Larson. 2024. S. 3404-3412 (IJCAI International Joint Conference on Artificial Intelligence).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Quantitative Claim-Centric Reasoning in Logic-Based Argumentation
AU - Hecher, Markus
AU - Mahmood, Yasir
AU - Meier, Arne
AU - Schmidt, Johannes
N1 - Publisher Copyright: © 2024 International Joint Conferences on Artificial Intelligence. All rights reserved.
PY - 2024
Y1 - 2024
N2 - 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 a 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.
AB - 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 a 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.
UR - http://www.scopus.com/inward/record.url?scp=85197342133&partnerID=8YFLogxK
M3 - Conference contribution
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 3404
EP - 3412
BT - Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
A2 - Larson, Kate
ER -