ntm1169@dsac.dla.mil (Mott Given) (12/14/89)
What are version spaces ( as used in learning theory and AI)?
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Mott Given @ Defense Logistics Agency Systems Automation Center,
DSAC-TMP, Bldg. 27-1, P.O. Box 1605, Columbus, OH 43216-5002
INTERNET: mgiven@dsac.dla.mil UUCP: ...{seismo!osu-cis}!dsacg1!mgiven
Phone: 614-238-9431 AUTOVON: 850-9431 FAX: 614-238-3214 I speak for myselfsarrett@ics.uci.edu (Wendy Sarrett) (12/15/89)
Basically with version spaces, instead of maintaining one hypothesis, you maintain a set of hypotheses consistant with the data. This is usually represented by it's boundary sets S and G. The S set is the most specific set of hypotheses consistant with the data and the G set is the most general hypotheses consistant with the data. The version space learning algorithms attempt to get the G and S sets to converge to one hypothesis. For more information, one reference is Tom Mitchell's 1982 Artificial Intelligence article entitled "Generalization as Search" (vol 18, pg 203-226).