Abstract
Lexicographic inference is a well-known and popular approach to reasoning with non-monotonic conditionals. It is a logic of very high-quality, as it extends rational closure and avoids the so-called drowning problem. It seems, however, this high quality comes at a cost, as reasoning on the basis of lexicographic inference is of high computational complexity. In this paper, we show that lexicographic inference satisfies syntax splitting, which means that we can restrict our attention to parts of the belief base that share atoms with a given query, thus seriously restricting the computational costs for many concrete queries. Furthermore, we make some observations on the relationship between c-representations and lexicographic inference, and reflect on the relation between syntax splitting and the drowning problem.
Original language | English |
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Title of host publication | Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence |
Editors | Luc De Raedt |
Publisher | International Joint Conferences on Artificial Intelligence |
Pages | 2662-2668 |
Number of pages | 7 |
ISBN (Electronic) | 978-1-956792-00-3 |
DOIs | |
Publication status | Published - 23 Jul 2022 |
Event | The Thirty-First International Joint Conference on Artificial Intelligence - Vienna University of Technology, Vienna, Austria Duration: 23 Jul 2022 → 29 Jul 2022 Conference number: 31 https://www.ijcai.org/proceedings/2022/ |
Conference
Conference | The Thirty-First International Joint Conference on Artificial Intelligence |
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Abbreviated title | IJCAI-22 |
Country/Territory | Austria |
City | Vienna |
Period | 23/07/22 → 29/07/22 |
Internet address |
Keywords
- Knowledge Representation and Reasoning: Non-monotonic Reasoning