{"type":"ScholarlyArticle","title":"Anytime Inference in Probabilistic Logic Programs with Tp-Compilation","authors":[{"name":"Jonas Vlasselaer","slug":"jonas-vlasselaer","given":"Jonas","family":"Vlasselaer","affiliation":""},{"name":"Guy Van den Broeck","slug":"guy-van-den-broeck","given":"Guy","family":"Van den Broeck","affiliation":""},{"name":"Angelika Kimmig","slug":"angelika-kimmig","given":"Angelika","family":"Kimmig","affiliation":""},{"name":"Wannes Meert","slug":"wannes-meert","given":"Wannes","family":"Meert","affiliation":""},{"name":"Luc De Raedt","slug":"luc-de-raedt","given":"Luc","family":"de Raedt","affiliation":""}],"abstract":"Existing techniques for inference in probabilistic logic programs are sequential: they first compute the relevant propositional formula for the query of interest, then compile it into a tractable target representation and finally, perform weighted model counting on the resulting representation. We propose Tp-compilation, a new inference technique based on forward reasoning. Tp-compilation proceeds incrementally in that it interleaves the knowledge compilation step for weighted model counting with forward reasoning on the logic program. This leads to a novel anytime algorithm that provides hard bounds on the inferred probabilities. Furthermore, an empirical evaluation shows that Tp-compilation effectively handles larger instances of complex real-world problems than current sequential approaches, both for exact and for anytime approximate inference.","doi":null,"url":"https://ijcai.org/proceedings/2015/263","pdf":"https://ijcai.org/proceedings/2015/0263.pdf","markdown":"https://ijcai.org/proceedings/2015/263.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/263","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Relational Learning","track":"Main Track","number":263,"pages":{"first":1852,"last":1857},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}