{"type":"ScholarlyArticle","title":"Using the Probabilistic Logic Programming Language P-log for Causal and Counterfactual Reasoning and Non-Naive Conditioning","authors":[{"name":"Chitta Baral","slug":"chitta-baral","given":"Chitta","family":"Baral","affiliation":""},{"name":"Matt Hunsaker","slug":"matt-hunsaker","given":"Matt","family":"Hunsaker","affiliation":""}],"abstract":"P-log is a probabilistic logic programming language, which combines both logic programming style knowledge representation and probabilistic reasoning. In earlier papers various advantages of P-log have been discussed. In this paper we further elaborate on the KR prowess of P-log by showing that: (i) it can be used for causal and counterfactual reasoning and (ii) it provides an elaboration tolerant way for non-naive conditioning.","doi":null,"url":"https://ijcai.org/proceedings/2007/37","pdf":"https://ijcai.org/proceedings/2007/0037.pdf","markdown":"https://ijcai.org/proceedings/2007/37.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/37","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":37,"pages":{"first":243,"last":248},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}