{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T16:42:46Z","timestamp":1762101766016},"reference-count":25,"publisher":"Cambridge University Press (CUP)","issue":"4-5","license":[{"start":{"date-parts":[[2015,9,3]],"date-time":"2015-09-03T00:00:00Z","timestamp":1441238400000},"content-version":"unspecified","delay-in-days":64,"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":[[2015,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper contributes to the area of inductive logic programming by presenting a new learning framework that allows the learning of weak constraints in Answer Set Programming (ASP). The framework, called<jats:italic>Learning from Ordered Answer Sets<\/jats:italic>, generalises our previous work on learning ASP programs without weak constraints, by considering a new notion of examples as<jats:italic>ordered<\/jats:italic>pairs of partial answer sets that exemplify which answer sets of a learned hypothesis (together with a given background knowledge) are<jats:italic>preferred<\/jats:italic>to others. In this new learning task inductive solutions are searched within a hypothesis space of normal rules, choice rules, and hard and weak constraints. We propose a new algorithm, ILASP2, which is sound and complete with respect to our new learning framework. We investigate its applicability to learning preferences in an interview scheduling problem and also demonstrate that when restricted to the task of learning ASP programs without weak constraints, ILASP2 can be much more efficient than our previously proposed system.<\/jats:p>","DOI":"10.1017\/s1471068415000198","type":"journal-article","created":{"date-parts":[[2015,9,3]],"date-time":"2015-09-03T08:21:21Z","timestamp":1441268481000},"page":"511-525","source":"Crossref","is-referenced-by-count":13,"title":["Learning weak constraints in answer set programming"],"prefix":"10.1017","volume":"15","author":[{"given":"MARK","family":"LAW","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"ALESSANDRA","family":"RUSSO","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"KRYSIA","family":"BRODA","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2015,9,3]]},"reference":[{"key":"S1471068415000198_ref17","unstructured":"Law M. , Russo A. and Broda K. 2015c. Simplified reduct for choice rules in ASP. Tech. Rep. DTR2015-2, Imperial College of Science, Technology and Medicine, Department of Computing."},{"key":"S1471068415000198_ref10","doi-asserted-by":"crossref","unstructured":"Geisler B. , Ha V. and Haddawy P. 2001. Modeling user preferences via theory refinement. In Proceedings of the 6th international conference on Intelligent user interfaces. ACM, 87\u201390.","DOI":"10.1145\/359784.360291"},{"key":"S1471068415000198_ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04238-6_16"},{"key":"S1471068415000198_ref11","first-page":"453","article-title":"A model of user preference learning for content-based recommender systems","volume":"28","author":"Horv\u00e1th","year":"2012","journal-title":"Computing and informatics"},{"key":"S1471068415000198_ref15","doi-asserted-by":"crossref","unstructured":"Law M. , Russo A. and Broda K. 2015a. The ILASP system for learning answer set programs. https:\/\/www.doc.ic.ac.uk\/~ml1909\/ILASP.","DOI":"10.1007\/978-3-319-11558-0_22"},{"key":"S1471068415000198_ref14","volume-title":"Logics in Artificial Intelligence (JELIA 2014)","author":"Law","year":"2014"},{"key":"S1471068415000198_ref21","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44797-0_16"},{"key":"S1471068415000198_ref23","doi-asserted-by":"publisher","DOI":"10.1093\/jigpal\/12.5.371"},{"key":"S1471068415000198_ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04238-6_75"},{"key":"S1471068415000198_ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-011-5259-2"},{"key":"S1471068415000198_ref16","unstructured":"Law M. , Russo A. and Broda K. 2015b. Proof of the soundness and completeness of ILASP2. https:\/\/www.doc.ic.ac.uk\/~ml1909\/Proofs_for_ILASP2.pdf."},{"key":"S1471068415000198_ref3","unstructured":"Calimeri F. , Faber W. , Gebser M. , Ianni G. , Kaminski R. , Krennwallner T. , Leone N. , Ricca F. and Schaub T. 2013. ASP-Core-2 input language format. https:\/\/www.mat.unical.it\/aspcomp2013\/files\/ASP-CORE-2.0.pdf."},{"key":"S1471068415000198_ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5113-y"},{"key":"S1471068415000198_ref18","doi-asserted-by":"publisher","DOI":"10.1007\/BF03037089"},{"key":"S1471068415000198_ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-39857-8_15"},{"key":"S1471068415000198_ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(98)00034-4"},{"key":"S1471068415000198_ref4","unstructured":"Corapi D. , Russo A. and Lupu E. 2010. Inductive logic programming as abductive search. In ICLP (Technical Communications). 54\u201363."},{"key":"S1471068415000198_ref20","first-page":"1551","volume-title":"Proceedings of the Twenty-Third international joint conference on Artificial Intelligence","author":"Muggleton","year":"2013"},{"key":"S1471068415000198_ref9","doi-asserted-by":"crossref","first-page":"107","DOI":"10.3233\/AIC-2011-0491","article-title":"Potassco: The Potsdam answer set solving collection","volume":"24","author":"Gebser","year":"2011","journal-title":"AI Communications"},{"key":"S1471068415000198_ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.jal.2008.10.007"},{"key":"S1471068415000198_ref6","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44682-6_10"},{"key":"S1471068415000198_ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-31951-8_12"},{"key":"S1471068415000198_ref25","unstructured":"Srinivasan A. 2001. The aleph manual. 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