{"type":"ScholarlyArticle","title":"OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models","authors":[{"name":"Manuel Arias","slug":"manuel-arias","given":"Manuel","family":"Arias","affiliation":"Universidad Nacional de Educación a Distancia (UNED) , Madrid , Spain"},{"name":"Jorge Pérez-Martín","slug":"jorge-perez-martin","given":"Jorge","family":"Pérez-Martín","affiliation":"Universidad Nacional de Educación a Distancia (UNED) , Madrid , Spain"},{"name":"Manuel Luque","slug":"manuel-luque","given":"Manuel","family":"Luque","affiliation":"Universidad Nacional de Educación a Distancia (UNED) , Madrid , Spain"},{"name":"Francisco J. Díez","slug":"francisco-j-diez","given":"Francisco J.","family":"Díez","affiliation":"Universidad Nacional de Educación a Distancia (UNED) , Madrid , Spain"}],"abstract":"OpenMarkov is a Java open-source tool for creating and evaluating probabilistic graphical models, including Bayesian networks, influence diagrams, and some Markov models. With more than 100,000 lines of code, it offers some features for interactive learning, explanation of reasoning, and cost-effectiveness analysis,  which are not available in any other tool. OpenMarkov has been used at universities, research centers, and large companies in more than 30 countries on four continents. Several models, some of them for real-world medical applications, built with OpenMarkov, are publicly available on Internet.","doi":"10.24963/ijcai.2019/931","url":"https://ijcai.org/proceedings/2019/931","pdf":"https://ijcai.org/proceedings/2019/0931.pdf","markdown":"https://ijcai.org/proceedings/2019/931.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/931","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Demos","track":"Demos","number":931,"pages":{"first":6485,"last":6487},"keywords":["AI: Machine Learning","Applications: Medical and healthcare","AI: Uncertainty in AI","AI: Programming for AI"],"videos":[],"references":[{"position":1,"raw":"[Arias and Díez, 2007] M. 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