Anti-unification and Generalization: A Survey

0576264 - ÚI 2024 RIV AT eng C - Conference Paper (international conference)
Cerna, David M. - Kutsia, T.
Anti-unification and Generalization: A Survey.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23). Vienna: International Joint Conferences on Artificial Intelligence, 2023 - (Elkind, E.), s. 6563-6573. ISBN 978-1-956792-03-4.
[IJCAI 2023: International Joint Conference on Artificial Intelligence /32./. Macao (MO), 19.08.2023-25.08.2023]
R&D Projects: GA ČR(CZ) GF22-06414L
Institutional support: RVO:67985807
Keywords : survey * Knowledge Representation and Reasoning * Multidisciplinary Topics and Applications
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://dx.doi.org/10.24963/ijcai.2023/736

Anti-unification (AU) is a fundamental operation for generalization computation used for inductive inference. It is the dual operation to unification, an operation at the foundation of automated theorem proving. Interest in AU from the AI and related communities is growing, but without a systematic study of the concept nor surveys of existing work, investigations often resort to developing application-specific methods that existing approaches may cover. We provide the first survey of AU research and its applications and a general framework for categorizing existing and future developments.
Permanent Link: https://hdl.handle.net/11104/0345832