{"type":"ScholarlyArticle","title":"Multiple Convergence: An Approach to Disjunctive Concept Acquisition","authors":[{"name":"K. S. Murray","slug":"k-s-murray","given":"K. S.","family":"Murray","affiliation":"Department of Computer Sciences The University of Texas at Austin Austin , Texas 78712"}],"abstract":"Multiple convergence is proposed as a method for acquiring disjunctive concept descriptions. Disjunctive descriptions are necessary when the concept representation language is insufficiently expressive to satisfy the .completeness and consistency requirements of inductive learning with a single conjunction of generalized features. Multiple convergence overcomes this insufficiency by allowing the disjuncts of a complex concept to be acquired independently. By summarizing correlations among features in the training data, disjunctive concepts can provide rich extensions to the representation language which may enhance subsequent learning. This paper presents the benefits of disjunctive concept descriptions and advocates multiple convergence as an approach to their acquisition. Multiple convergence has been implemented in the learning system HYDRA, and a detailed example of its execution is presented.","doi":null,"url":"https://ijcai.org/proceedings/1987/61","pdf":"https://ijcai.org/proceedings/1987/0061.pdf","markdown":"https://ijcai.org/proceedings/1987/61.md","bibtex":"https://ijcai.org/proceedings/1987/bibtex/61","volume":{"slug":"1987","title":"Proceedings of the Tenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1987","url":"https://ijcai.org/proceedings/1987/","year":1987,"location":"Milan, Italy","dates":"","editors":"John McDermott","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Knowledge Acquisition","track":"Knowledge Acquisition","number":61,"pages":{"first":297,"last":299},"keywords":[],"videos":[],"references":[{"position":1,"raw":"Bundy, A., Silver, B., and Plummer, D. An Analytical Comparison of Some Rule-Learnin~ Programs. Artificial Intelligence, Vol. 27(2) (1985).","title":"An Analytical Comparison of Some Rule-Learnin~ Programs","authors":"A Bundy, B Silver, D Plummer","year":"1985","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"Dietterich, T. and Michalski, R. A Compara- tive Review of Selected Methods for Learning. In Machine Learning, Tioga Publishing, 1983.","title":"A Comparative Review of Selected Methods for Learning","authors":"T Dietterich, R Michalski","year":"1983","venue":"Machine Learning","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"lba, G. Learning Disjunctive Concepts From Examples. A.l. Memo 548, MIT AI Lab, 1979.","title":"Learning Disjunctive Concepts From Examples","authors":"G","year":"1979","venue":"A.l. Memo","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"Michalski, R. A Theory and Methodology of Inductive Learning. In Machine Learning, Michalski, R., Carbonell, J., and Mitchell, •T . (eds.), Tioga Publishing, 1983.","title":"A Theory and Methodology of Inductive Learning","authors":"R Michalski","year":"1983","venue":"Machine Learning","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"Mitchell, T.M. Version Spaces: An Approach to Concept Learning, PhD Dissertation, Com- puter Science Department, Stanford University. (TR STAN-CS-78-711), 1978.","title":"Version Spaces: An Approach to Concept Learning","authors":"T M Mitchell","year":"1978","venue":null,"doi":null,"url":null,"internal_url":null},{"position":6,"raw":"Mitchell, T.M. Generalization as Search. Arti- ficial Intelligence, Volume 18 (1982), 203-226.","title":"Generalization as Search","authors":"T M Mitchell","year":"1982","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"Smith, E. and Medin, D. Categories and Con- cepts, Cambridge: Harvard University Press, 1981.","title":"Categories and Concepts","authors":"E Smith, D Medin","year":"1981","venue":null,"doi":null,"url":null,"internal_url":null},{"position":8,"raw":"Utgoff, P.E. Shift of Bias for Inductive Concept Learning. In Machine Learning, Michalski, R., Carbonell, J., and Mitchell, T. (eds.), Morgan Kaufmann, Vol. 2, 1986.","title":"Shift of Bias for Inductive Concept Learning","authors":"P E Utgoff","year":"1986","venue":"Machine Learning","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"deering power","title":"deering power","authors":null,"year":null,"venue":null,"doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}