{"type":"ScholarlyArticle","title":"Version Spaces: A Candidate Elimination Approach to Rule Learning","authors":[{"name":"Tom M. Mitchell","slug":"tom-m-mitchell","given":"Tom M.","family":"Mitchell","affiliation":""}],"abstract":"An important research problem in artificial intelligence is the study of methods for learning general concepts or rules from a set of training instances. An approach to this problem is presented which is guaranteed to find, without backtracking, all rule versions consistent with a set of positive and negative training instances. The algorithm put forth uses a representation of the space of those rules consistent with the observed training data. This \"rule version space\" is modified in response to new training instances by eliminating candidate rule versions found to conflict with each new instance. The use of version spaces is discussed in the context of Meta-DENDRAL, a program which learns rules in the domain of chemical spectroscopy.","doi":null,"url":"https://ijcai.org/proceedings/1977/68","pdf":"https://ijcai.org/proceedings/1977/0068.pdf","markdown":"https://ijcai.org/proceedings/1977/68.md","bibtex":"https://ijcai.org/proceedings/1977/bibtex/68","volume":{"slug":"1977","title":"Proceedings of the Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1977","url":"https://ijcai.org/proceedings/1977/","year":1977,"location":"Cambridge, MA, USA","dates":"","editors":"Raj Reddy","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Knowledge Acquisition","track":"Knowledge Acquisition","number":68,"pages":{"first":305,"last":309},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}