ACCELERATING SEARCH IN FUNCTION INDUCTION

dc.contributor.authorPhan, Thong H.eng
dc.contributor.authorWitten, Ian Heng
dc.date.accessioned2008-05-26T20:47:44Z
dc.date.available2008-05-26T20:47:44Z
dc.date.computerscience1999-05-27eng
dc.date.issued1989-11-01eng
dc.description.abstractInducing functions from examples is an important requirement in many learning systems. Blind search is the most general approach, but is vastly less efficient than specialized problem-solving methods. This paper presents a new strategy to accelerate search without sacrificing generality. Experiments with numeric functions show several orders of magnitude performance increase over the standard search technique. Two factors account for this improvement. First, the new strategy manipulates functions in groups instead of singly, so that many can be selected or discarded with only one comparison. Second, functional equivalence is handled automatically by the internal organization of search space.eng
dc.description.notesWe are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.caeng
dc.identifier.department1989-372-34eng
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/31132
dc.identifier.urihttp://hdl.handle.net/1880/46613
dc.language.isoEngeng
dc.publisher.corporateUniversity of Calgaryeng
dc.publisher.facultyScienceeng
dc.subjectComputer Scienceeng
dc.titleACCELERATING SEARCH IN FUNCTION INDUCTIONeng
dc.typeunknown
thesis.degree.disciplineComputer Scienceeng
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