{"type":"ScholarlyArticle","title":"Generalized Safe Conditional Syntax Splitting of Belief Bases","authors":[{"name":"Lars-Phillip Spiegel","slug":"lars-phillip-spiegel","given":"Lars-Phillip","family":"Spiegel","affiliation":""},{"name":"Jonas Haldimann","slug":"jonas-haldimann","given":"Jonas","family":"Haldimann","affiliation":""},{"name":"Jesse Heyninck","slug":"jesse-heyninck","given":"Jesse","family":"Heyninck","affiliation":""},{"name":"Gabriele Kern-Isberner","slug":"gabriele-kern-isberner","given":"Gabriele","family":"Kern-Isberner","affiliation":""},{"name":"Christoph Beierle","slug":"christoph-beierle","given":"Christoph","family":"Beierle","affiliation":""}],"abstract":"Splitting techniques in knowledge representation\r\nhelp focus on relevant parts of a belief base and\r\nreduce the complexity of reasoning generally. In\r\nthis paper, we propose a generalization of safe conditional syntax splittings that broadens the applicability of splitting postulates for inductive inference from belief bases. In contrast to safe conditional syntax splitting, our generalized notion supports syntax splittings of a belief base ∆ where the\r\nsubbases of ∆ may share atoms and nontrivial conditionals. We illustrate how this new notion overcomes limitations of previous splitting concepts,\r\nand we identify genuine splittings, separating them\r\nfrom simple splittings that do not provide benefits\r\nfor inductive inference from ∆. We introduce adjusted inference postulates based on our generalization of conditional syntax splitting. We evaluate\r\nseveral inductive inference operators with respect\r\nto these postulates, and show that generalized safe\r\nconditional syntax splitting is a strictly stronger requirement for inductive inference operators, covering more syntax splitting applications.","doi":"10.24963/ijcai.2025/521","url":"https://ijcai.org/proceedings/2025/521","pdf":"https://ijcai.org/proceedings/2025/0521.pdf","markdown":"https://ijcai.org/proceedings/2025/521.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/521","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Knowledge Representation and Reasoning","track":"Main Track","number":521,"pages":{"first":4678,"last":4686},"keywords":["Knowledge Representation and Reasoning: KRR: Non-monotonic reasoning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}