{"title":"Optimizing general chain programs","authors":"Anke D. Rieger","doi":"10.1016/S0743-1066(99)00020-5","DOIUrl":null,"url":null,"abstract":"<div><p>The goal of knowledge compilation is to transform programs in order to speed up their evaluation. In Inductive Logic Programming, two major approaches to speed-up learning exist: Approaches that intertwine the learning and the optimization process and approaches that separate these two processes. We follow the latter approach and present a new equivalence-preserving transformation method for programs with ordered clauses. It eliminates redundancies that make forward inference procedures slow. We introduce general chain rules, a specific class of ordered clauses, whose syntactical features are exploited in a new forward inference method. The comparison of the time needed by this method to evaluate the transformed program with the time needed by a standard forward inference procedure for the original program confirms the expected speed-up.</p></div>","PeriodicalId":101236,"journal":{"name":"The Journal of Logic Programming","volume":"40 2","pages":"Pages 251-271"},"PeriodicalIF":0.0000,"publicationDate":"1999-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0743-1066(99)00020-5","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Logic Programming","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0743106699000205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The goal of knowledge compilation is to transform programs in order to speed up their evaluation. In Inductive Logic Programming, two major approaches to speed-up learning exist: Approaches that intertwine the learning and the optimization process and approaches that separate these two processes. We follow the latter approach and present a new equivalence-preserving transformation method for programs with ordered clauses. It eliminates redundancies that make forward inference procedures slow. We introduce general chain rules, a specific class of ordered clauses, whose syntactical features are exploited in a new forward inference method. The comparison of the time needed by this method to evaluate the transformed program with the time needed by a standard forward inference procedure for the original program confirms the expected speed-up.