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dc.contributor.authorElkan, Charles P.en_US
dc.contributor.authorSegre, Alberto M.en_US
dc.date.accessioned2007-04-23T17:36:40Z
dc.date.available2007-04-23T17:36:40Z
dc.date.issued1989-05en_US
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR89-1010en_US
dc.identifier.urihttps://hdl.handle.net/1813/6810
dc.description.abstractThis paper describes a new domain-independent explanation-based learning (EBL) algorithm that is able to acquire useful new rules in situations where previous EBL algorithms would fail. The new algorithm is complete in the sense that every valid rule that can be extracted from an explanation can be extracted by this algorithm. The new algorithm is described inside a framework that provides insight into how the design of successful EBL systems takes into account operationality and imperfect domain theory issues.en_US
dc.format.extent1370004 bytes
dc.format.extent291363 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleNot the Last Word on EBL Algorithmsen_US
dc.typetechnical reporten_US


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