{"type":"ScholarlyArticle","title":"On the Learnability of Possibilistic Theories","authors":[{"name":"Cosimo Persia","slug":"cosimo-persia","given":"Cosimo","family":"Persia","affiliation":"University of Bergen"},{"name":"Ana Ozaki","slug":"ana-ozaki","given":"Ana","family":"Ozaki","affiliation":"University of Bergen"}],"abstract":"We investigate learnability of possibilistic theories from entailments in light of Angluin’s exact learning model. We consider cases in which only membership, only equivalence, and both kinds of queries can be posed by the learner. We then show that, for a large class of problems, polynomial time learnability results for classical logic can be transferred to the respective possibilistic extension. In particular, it follows from our results that the possibilistic extension of propositional Horn theories is exactly learnable in polynomial time. As polynomial time learnability in the exact model is transferable to the classical probably approximately correct (PAC) model extended with membership queries, our work also establishes such results in this model.","doi":"10.24963/ijcai.2020/259","url":"https://ijcai.org/proceedings/2020/259","pdf":"https://ijcai.org/proceedings/2020/0259.pdf","markdown":"https://ijcai.org/proceedings/2020/259.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/259","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":259,"pages":{"first":1870,"last":1876},"keywords":["Uncertainty in AI: Uncertainty Representations","Machine Learning: Learning Theory","Knowledge Representation and Reasoning: Logics for Knowledge Representation"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/24997/file_24997.m3u8","length_sec":300,"provider":"hls"}],"references":[{"position":1,"raw":"[Agarwal and Nayal, 2015] Parul Agarwal and Dr. H. 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