{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/encoding-markov-logic-networks-in","title":"Encoding Markov Logic Networks in Possibilistic Logic","arxiv_id":"1506.01432","date":"2015-06-03","proceeding":null,"authors":["Ondrej Kuzelka","Jesse Davis","Steven Schockaert"],"abstract":"Markov logic uses weighted formulas to compactly encode a probability\ndistribution over possible worlds. Despite the use of logical formulas, Markov\nlogic networks (MLNs) can be difficult to interpret, due to the often\ncounter-intuitive meaning of their weights. To address this issue, we propose a\nmethod to construct a possibilistic logic theory that exactly captures what can\nbe derived from a given MLN using maximum a posteriori (MAP) inference.\nUnfortunately, the size of this theory is exponential in general. We therefore\nalso propose two methods which can derive compact theories that still capture\nMAP inference, but only for specific types of evidence. These theories can be\nused, among others, to make explicit the hidden assumptions underlying an MLN\nor to explain the predictions it makes.","url_abs":"http://arxiv.org/abs/1506.01432v2","url_pdf":"http://arxiv.org/pdf/1506.01432v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"encoding-markov-logic-networks-in","repo_url":"https://github.com/supertweety/mln2poss","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}