Abstract
Assumption-based argumentation (ABA) is an argumentative formalism that allows for reasoning on the basis of defeasible assumptions and strict rules. Standard semantics for this formalism sometimes give rise to problematic behaviour in the presence of rules with assumptions in their heads. In this paper, we introduce a six-valued labelling semantics that overcomes these shortcomings while preserving all the usual properties of the standard Dung-style three-valued semantics for ABA frameworks, including existence of the complete semantics, uniqueness of the grounded semantics, and preservation of the computational complexity of all the main reasoning processes.
| Original language | English |
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| Title of host publication | Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
| Editors | Kate Larson |
| Publisher | International Joint Conferences on Artificial Intelligence |
| Pages | 3413-3420 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781956792041 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 - Jeju, Korea, Republic of Duration: 3 Aug 2024 → 9 Aug 2024 https://ijcai24.org/ |
Publication series
| Series | IJCAI International Joint Conference on Artificial Intelligence |
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| ISSN | 1045-0823 |
Conference
| Conference | 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024 |
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| Abbreviated title | IJCAI 202 |
| Country/Territory | Korea, Republic of |
| City | Jeju |
| Period | 3/08/24 → 9/08/24 |
| Internet address |