{"type":"ScholarlyArticle","title":"A Model of Decidable Introspective Reasoning with Quantifying-In","authors":[{"name":"Gerhard Lakemeyer","slug":"gerhard-lakemeyer","given":"Gerhard","family":"Lakemeyer","affiliation":""}],"abstract":"Since knowledge is usually incomplete, agents need to introspect on what they know and do not know . The best known models of introspective reasoning suffer from intractability or even undecidability if the underlying language is first-order . To better suit the fact that agents have limited resources, we recently proposed a model of decidable introspective reasoning in first-order knowledge bases (KBs). However, this model is deficient in that it does not allow for quantifying-in, which is needed to distinguish between knowing that and knowing who. In this paper, we extend our earlier work by adding quantifying-in and equality to a model of limited belief that integrates ideas from possible-world semantics and relevance logic.","doi":null,"url":"https://ijcai.org/proceedings/1991/74","pdf":"https://ijcai.org/proceedings/1991/0074.pdf","markdown":"https://ijcai.org/proceedings/1991/74.md","bibtex":"https://ijcai.org/proceedings/1991/bibtex/74","volume":{"slug":"1991","title":"Proceedings of the Twelfth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1991","url":"https://ijcai.org/proceedings/1991/","year":1991,"location":"Sydney, New South Wales, Australia","dates":"24-30 August 1991","editors":"John Mylopoulos and Ray Reiter","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Knowledge Representation","track":"Knowledge Representation","number":74,"pages":{"first":492,"last":496},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}