{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T06:45:23Z","timestamp":1778827523017,"version":"3.51.4"},"reference-count":23,"publisher":"Cambridge University Press (CUP)","issue":"5","license":[{"start":{"date-parts":[[2021,11,5]],"date-time":"2021-11-05T00:00:00Z","timestamp":1636070400000},"content-version":"unspecified","delay-in-days":65,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Theory and Practice of Logic Programming"],"published-print":{"date-parts":[[2021,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper explores the integration of hypothetical reasoning into an efficient implementation of the fuzzy logic language Bousi<jats:italic>\u223c<\/jats:italic>Prolog. To this end, we first analyse what would be expected from a logic inference system, equipped with what is called embedded implication, to model solving goals with respect to assumptions. We start with a propositional system and incrementally build more complex systems and implementations to satisfy the requirements imposed by a system like Bousi<jats:italic>\u223c<\/jats:italic>Prolog. Finally, we propose an inference system, operational semantics and the translation function to generate efficient Prolog programmes from Bousi<jats:italic>\u223c<\/jats:italic>Prolog programmes.<\/jats:p>","DOI":"10.1017\/s1471068421000405","type":"journal-article","created":{"date-parts":[[2021,11,5]],"date-time":"2021-11-05T14:49:45Z","timestamp":1636123785000},"page":"680-697","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":2,"title":["Planning for an Efficient Implementation of Hypothetical Bousi\u223cProlog"],"prefix":"10.1017","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6482-3220","authenticated-orcid":false,"given":"PASCUAL","family":"JULI\u00c1N-IRANZO","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6075-4398","authenticated-orcid":false,"given":"FERNANDO","family":"S\u00c1ENZ-P\u00c9REZ","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2021,11,5]]},"reference":[{"key":"S1471068421000405_ref5","unstructured":"Cuijpers, P. 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A novel fuzzy expert system for the identification of severity of carpal tunnel syndrome. BioMed Research International 2013. Loia, V., Senatore, S. and Sessa, M. I. 2001. Similarity-based SLD resolution and its implementation in an extended Prolog system. In International Conference on Fuzzy Systems (FUZZ-IEEE). 650\u2013653."},{"key":"S1471068421000405_ref20","doi-asserted-by":"publisher","DOI":"10.3233\/IFS-130834"},{"key":"S1471068421000405_ref6","doi-asserted-by":"crossref","unstructured":"Fontana, F. A. and Formato, F. 1999. Likelog: A logic programming language for flexible data retrieval. 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A model for criminal decision making based on hypothetical reasoning about the future. In IEA\/AIE 2009, Taiwan, June 24\u201327. LNCS, vol. 5579. 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