{"type":"ScholarlyArticle","title":"Learning Procedures from Examples and by Doing","authors":[{"name":"David M. Neves","slug":"david-m-neves","given":"David M.","family":"Neves","affiliation":"Computer Sciences Department University of Wisconsin -Madison Madison , WI 53706"}],"abstract":"This paper de sc ribes a program that learns procedures hv examining worked-out ex~mples in a textbook ;md hv working problem s. Two kinds of production ( lf~lh<'ll) rules are created: ll'orl.ing .li\"word rule s that produce an action when a procedure is executed ~nd dif/('r<'IIC<' rules that suggest operators from observed transformations. Durin g example leilrning . the progrllm examines tvvo states in an example, figures out the operator that produced the second state and creates a production with some part of the first line in the condition with the operator in the action. During learning 11\\ wo rking problems , the program generates its own example trace by problem so lv ing and uses the same example learning techniques.","doi":null,"url":"https://ijcai.org/proceedings/1985/120","pdf":"https://ijcai.org/proceedings/1985/0120.pdf","markdown":"https://ijcai.org/proceedings/1985/120.md","bibtex":"https://ijcai.org/proceedings/1985/bibtex/120","volume":{"slug":"1985","title":"Proceedings of the Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1985","url":"https://ijcai.org/proceedings/1985/","year":1985,"location":"Los Angeles, California, USA","dates":"","editors":"Aravind Joshi","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Learning and Acquisition","track":"Learning and Acquisition","number":120,"pages":{"first":624,"last":629},"keywords":[],"videos":[],"references":[{"position":1,"raw":"Anderson, .l . R. lile orchilecll•re or cognilion. 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