{"title":"当地紧缺计划","authors":"JORGE FANDINNO, VLADIMIR LIFSCHITZ, NATHAN TEMPLE","doi":"10.1017/s147106842300039x","DOIUrl":null,"url":null,"abstract":"<p>Program completion is a translation from the language of logic programs into the language of first-order theories. Its original definition has been extended to programs that include integer arithmetic, accept input, and distinguish between output predicates and auxiliary predicates. For tight programs, that generalization of completion is known to match the stable model semantics, which is the basis of answer set programming. We show that the tightness condition in this theorem can be replaced by a less restrictive “local tightness” requirement. From this fact we conclude that the proof assistant <span>anthem-p2p</span> can be used to verify equivalence between locally tight programs.</p>","PeriodicalId":49436,"journal":{"name":"Theory and Practice of Logic Programming","volume":"84 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Locally Tight Programs\",\"authors\":\"JORGE FANDINNO, VLADIMIR LIFSCHITZ, NATHAN TEMPLE\",\"doi\":\"10.1017/s147106842300039x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Program completion is a translation from the language of logic programs into the language of first-order theories. Its original definition has been extended to programs that include integer arithmetic, accept input, and distinguish between output predicates and auxiliary predicates. For tight programs, that generalization of completion is known to match the stable model semantics, which is the basis of answer set programming. We show that the tightness condition in this theorem can be replaced by a less restrictive “local tightness” requirement. From this fact we conclude that the proof assistant <span>anthem-p2p</span> can be used to verify equivalence between locally tight programs.</p>\",\"PeriodicalId\":49436,\"journal\":{\"name\":\"Theory and Practice of Logic Programming\",\"volume\":\"84 1\",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-01-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theory and Practice of Logic Programming\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1017/s147106842300039x\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory and Practice of Logic Programming","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1017/s147106842300039x","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Program completion is a translation from the language of logic programs into the language of first-order theories. Its original definition has been extended to programs that include integer arithmetic, accept input, and distinguish between output predicates and auxiliary predicates. For tight programs, that generalization of completion is known to match the stable model semantics, which is the basis of answer set programming. We show that the tightness condition in this theorem can be replaced by a less restrictive “local tightness” requirement. From this fact we conclude that the proof assistant anthem-p2p can be used to verify equivalence between locally tight programs.
期刊介绍:
Theory and Practice of Logic Programming emphasises both the theory and practice of logic programming. Logic programming applies to all areas of artificial intelligence and computer science and is fundamental to them. Among the topics covered are AI applications that use logic programming, logic programming methodologies, specification, analysis and verification of systems, inductive logic programming, multi-relational data mining, natural language processing, knowledge representation, non-monotonic reasoning, semantic web reasoning, databases, implementations and architectures and constraint logic programming.