Repairing Learned Knowledge Using Experience

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6553

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DC Field	Value	Language
dc.creator	Winston, Patrick H.	-
dc.creator	Rao, Satayjit	-
dc.date	2004-10-04T15:31:16Z	-
dc.date	2004-10-04T15:31:16Z	-
dc.date	1990-05-01	-
dc.date.accessioned	2013-10-09T02:45:57Z	-
dc.date.available	2013-10-09T02:45:57Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1231	-
dc.identifier	http://hdl.handle.net/1721.1/6553	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	Explanation-based learning occurs when something useful is retained from an explanation, usually an account of how some particular problem can be solved given a sound theory. Many real-world explanations are not based on sound theory, however, and wrong things may be learned accidentally, as subsequent failures will likely demonstrate. In this paper, we describe ways to isolate the facts that cause failures, ways to explain why those facts cause problems, and ways to repair learning mistakes. In particular, our program learns to distinguish pails from cups after making a few mistakes.	-
dc.format	1984828 bytes	-
dc.format	776339 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1231	-
dc.title	Repairing Learned Knowledge Using Experience	-
Appears in Collections:	MIT Items

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