%0 Conference Paper %1 sato1995statistical %A Sato, Taisuke %B IN PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LOGIC PROGRAMMING (ICLP’95 %D 1995 %I MIT Press %K ml proposal tau %P 715--729 %T A Statistical Learning Method for Logic Programs with Distribution Semantics %U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.4408 %X When a joint distribution PF is given to a set F of facts in a logic program DB = F U R where R is a set of rules, we can further extend it to a joint distribution PDB over the set of possible least models of DB. We then define the semantics of DB with the associated distribution PF as PDB, and call it distribution semantics. While the

@inproceedings{sato1995statistical, abstract = {When a joint distribution PF is given to a set F of facts in a logic program DB = F U R where R is a set of rules, we can further extend it to a joint distribution PDB over the set of possible least models of DB. We then define the semantics of DB with the associated distribution PF as PDB, and call it distribution semantics. While the}, added-at = {2016-11-28T14:14:31.000+0100}, author = {Sato, Taisuke}, biburl = {https://www.bibsonomy.org/bibtex/204ecf45b4d33c0a07a90628fff5cecfe/machinelearning}, booktitle = {IN PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LOGIC PROGRAMMING (ICLP’95}, description = {CiteSeerX — A Statistical Learning Method for Logic Programs with Distribution Semantics}, interhash = {77521b77089f7ae7406c36603f9bee83}, intrahash = {04ecf45b4d33c0a07a90628fff5cecfe}, keywords = {ml proposal tau}, pages = {715--729}, publisher = {MIT Press}, timestamp = {2016-11-28T14:14:31.000+0100}, title = {A Statistical Learning Method for Logic Programs with Distribution Semantics}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.4408}, year = 1995 }