Abstract
Syntax splitting is a property of inductive inference operators that ensures we can restrict our attention to parts of the conditional belief base that share atoms with a given query. To apply syntax splitting, a conditional belief base needs to consist of syntactically disjoint conditionals. This requirement is often too strong in practice, as conditionals might share atoms. In this paper we introduce the concept of conditional syntax splitting, inspired by the notion of conditional independence as known from probability theory. We show that lexicographic inference and system W satisfy conditional syntax splitting, and connect conditional syntax splitting to several known properties from the literature on non-monotonic reasoning, including the drowning effect.
Original language | English |
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Title of host publication | Proceedings of the 37th AAAI Conference on Artificial Intelligence |
Editors | Brian Williams, Yiling Chen, Jennifer Neville |
Publisher | AAAI Press |
Pages | 6416-6424 |
Number of pages | 9 |
Volume | 37 |
Edition | 5 |
ISBN (Electronic) | 9781577358800 |
DOIs | |
Publication status | Published - 27 Jun 2023 |
Event | 37th AAAI Conference on Artificial Intelligence - Washington, United States Duration: 7 Feb 2023 → 14 Feb 2023 Conference number: 37 |
Publication series
Series | AAAI Conference on Artificial Intelligence. Conference Proceedings |
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Volume | 37 |
Conference
Conference | 37th AAAI Conference on Artificial Intelligence |
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Abbreviated title | AAAI 2023 |
Country/Territory | United States |
City | Washington |
Period | 7/02/23 → 14/02/23 |