{"type":"ScholarlyArticle","title":"Inductive Inference Theory - A Unified Approach to Problems in Pattern Recognition and Artificial Intelligence","authors":[{"name":"R. Solomonott","slug":"r-solomonott","given":"R.","family":"Solomonott","affiliation":""}],"abstract":"Recent results in in:iuction theory are reviewed that demonstrate the general adequacy of the induction system of Solomoncff ar.d Willis. Several problems in pattern recognition and A.I. are investigated through these methods. The theory is used to obtain the a priori probabilities that are necessary in the application cf st.ochastic languages to pattern recognition. A simple, quantitative solution is presentee for part of Winston's problem of learning structural descriptions from examples. In c ont.ra~t to work :l n non-prcbabi .listic prediction, the present methods give probability values that can be usee with decision theory to make critical decisions.","doi":null,"url":"https://ijcai.org/proceedings/1975/42","pdf":"https://ijcai.org/proceedings/1975/0042.pdf","markdown":"https://ijcai.org/proceedings/1975/42.md","bibtex":"https://ijcai.org/proceedings/1975/bibtex/42","volume":{"slug":"1975","title":"Proceedings of the Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1975","url":"https://ijcai.org/proceedings/1975/","year":1975,"location":"Tbilisi, Georgia, USSR","dates":"","editors":"Patrick Winston and Carl Hewitt","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Learning Debugging And Automatic Programming","track":"Learning Debugging And Automatic Programming","number":42,"pages":{"first":274,"last":279},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}