{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T10:33:50Z","timestamp":1689676430436},"reference-count":23,"publisher":"Cambridge University Press (CUP)","issue":"3-4","license":[{"start":{"date-parts":[[2018,8,10]],"date-time":"2018-08-10T00:00:00Z","timestamp":1533859200000},"content-version":"unspecified","delay-in-days":40,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Theory and Practice of Logic Programming"],"published-print":{"date-parts":[[2018,7]]},"abstract":"Abstract<\/jats:title>We present a probabilistic extension of action language${\\cal BC}$+$<\/jats:tex-math><\/jats:alternatives><\/jats:inline-formula>. Just like${\\cal BC}$+$<\/jats:tex-math><\/jats:alternatives><\/jats:inline-formula>is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we callp<\/jats:italic>${\\cal BC}$+$<\/jats:tex-math><\/jats:alternatives><\/jats:inline-formula>, is defined as a high-level notation of LPMLN<\/jats:sup>programs\u2014a probabilistic extension of answer set programs. We show how probabilistic reasoning about transition systems, such as prediction, postdiction, and planning problems, as well as probabilistic diagnosis for dynamic domains, can be modeled inp<\/jats:italic>${\\cal BC}$+$<\/jats:tex-math><\/jats:alternatives><\/jats:inline-formula>and computed using an implementation of LPMLN<\/jats:sup>.<\/jats:p>","DOI":"10.1017\/s1471068418000303","type":"journal-article","created":{"date-parts":[[2018,8,10]],"date-time":"2018-08-10T05:44:17Z","timestamp":1533879857000},"page":"607-622","source":"Crossref","is-referenced-by-count":5,"title":["A Probabilistic Extension of Action Language"],"prefix":"10.1017","volume":"18","author":[{"given":"JOOHYUNG","family":"LEE","sequence":"first","affiliation":[]},{"given":"YI","family":"WANG","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2018,8,10]]},"reference":[{"key":"S1471068418000303_ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2002.12.001"},{"key":"S1471068418000303_ref2","doi-asserted-by":"crossref","unstructured":"Babb J. and Lee J. 2015. Action language ${$\\cal BC$}+$ . Journal of Logic and Computation, exv062.","DOI":"10.1093\/logcom\/exv062"},{"key":"S1471068418000303_ref10","first-page":"195","article-title":"Action languages5","volume":"3","author":"Gelfond","year":"1998","journal-title":"Electronic Transactions on Artificial Intelligence"},{"key":"S1471068418000303_ref6","unstructured":"Baral C. , Tran N. , and Tuan L.-C. 2002. Reasoning about actions in a probabilistic setting. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 507\u2013512."},{"key":"S1471068418000303_ref22","unstructured":"Younes H. L. and Littman M. L. 2004. PPDDL1. 0: An extension to PDDL for expressing planning domains with probabilistic effects."},{"key":"S1471068418000303_ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-24908-2_19"},{"key":"S1471068418000303_ref7","doi-asserted-by":"crossref","unstructured":"D'Asaro F. A. , Bikakis A. , Dickens L. , and Miller R. 2017. Foundations for a probabilistic event calculus. CoRR abs\/1703.06815.","DOI":"10.1007\/978-3-319-61660-5_7"},{"key":"S1471068418000303_ref9","doi-asserted-by":"publisher","DOI":"10.1016\/0743-1066(93)90035-F"},{"key":"S1471068418000303_ref19","doi-asserted-by":"crossref","unstructured":"Lee J. and Wang Y. 2018. Online appendix for the paper \u201cA probabilistic extension of action language ${$\\cal BC$}+$ \u201d.","DOI":"10.29007\/7fmn"},{"key":"S1471068418000303_ref18","unstructured":"Lee J. and Wang Y. 2016. Weighted rules under the stable model semantics. In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR). 145\u2013154."},{"key":"S1471068418000303_ref5","unstructured":"Baral C. , Mcilraith S. , and Son T. 2000. Formulating diagnostic problem solving using an action language with narratives and sensing."},{"key":"S1471068418000303_ref23","unstructured":"Zhu W. 2012. Plog: Its algorithms and applications. Ph.D. thesis, Texas Tech University."},{"key":"S1471068418000303_ref4","first-page":"21","volume-title":"Logic Programming and Nonmonotonic Reasoning","author":"Baral","year":"2004"},{"key":"S1471068418000303_ref16","doi-asserted-by":"crossref","unstructured":"Lee J. , Talsania S. , and Wang Y. 2017. Computing LPMLN using ASP and MLN solvers. Theory and Practice of Logic Programming.","DOI":"10.1017\/S1471068417000400"},{"key":"S1471068418000303_ref12","unstructured":"Giunchiglia E. and Lifschitz V. 1998. An action language based on causal explanation: Preliminary report. In Proceedings of National Conference on Artificial Intelligence (AAAI). AAAI Press, 623\u2013630."},{"key":"S1471068418000303_ref8","unstructured":"Eiter T. and Lukasiewicz T. 2003. Probabilistic reasoning about actions in nonmonotonic causal theories. In Proceedings Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI-2003). Morgan Kaufmann Publishers, 192\u2013199."},{"key":"S1471068418000303_ref1","doi-asserted-by":"crossref","unstructured":"Babb J. and Lee J. 2013. Cplus2ASP: Computing action language ${\\cal C}+}$ in answer set programming. In Proceedings of International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR). 122\u2013134.","DOI":"10.1007\/978-3-642-40564-8_13"},{"key":"S1471068418000303_ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-006-5833-1"},{"key":"S1471068418000303_ref13","first-page":"31","article-title":"History-based diagnosis templates in the framework of the situation calculus","volume":"15","author":"Iwan","year":"2002","journal-title":"AI Communications"},{"key":"S1471068418000303_ref17","unstructured":"Lee J. and Wang Y. 2015. A probabilistic extension of the stable model semantics. In International Symposium on Logical Formalization of Commonsense Reasoning, AAAI 2015 Spring Symposium Series."},{"key":"S1471068418000303_ref3","doi-asserted-by":"publisher","DOI":"10.1017\/S1471068403001807"},{"key":"S1471068418000303_ref15","unstructured":"Lee J. and Meng Y. 2013. Answer set programming modulo theories and reasoning about continuous changes. In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI)."},{"key":"S1471068418000303_ref14","unstructured":"Lee J. , Lifschitz V. , and Yang F. 2013. Action language ${$\\cal BC$}$ : Preliminary report. In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI)."}],"container-title":["Theory and Practice of Logic Programming"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1471068418000303","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T23:27:12Z","timestamp":1571700432000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1471068418000303\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":23,"journal-issue":{"issue":"3-4","published-print":{"date-parts":[[2018,7]]}},"alternative-id":["S1471068418000303"],"URL":"https:\/\/doi.org\/10.1017\/s1471068418000303","relation":{},"ISSN":["1471-0684","1475-3081"],"issn-type":[{"value":"1471-0684","type":"print"},{"value":"1475-3081","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7]]}}}