{"type":"ScholarlyArticle","title":"Logic-Based Inductive Synthesis of Efficient Programs","authors":[{"name":"Andrew Cropper","slug":"andrew-cropper","given":"Andrew","family":"Cropper","affiliation":""}],"abstract":"Inductive programming approaches typically rely on an Occamist bias to select hypotheses with minimal textual complexity. This approach, however, fails to distinguish between the efficiencies of hypothesised programs, such as merge sort (O(n log n)) and bubble sort (O(n2)). We address this issue by introducing techniques to learn logic programs with minimal resource complexity. We describe an algorithm proven to learn minimal resource complexity robot strategies, and we propose future work to generalise the approach to a broader class of programs.","doi":null,"url":"https://ijcai.org/proceedings/2016/564","pdf":"https://ijcai.org/proceedings/2016/0564.pdf","markdown":"https://ijcai.org/proceedings/2016/564.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/564","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":564,"pages":{"first":3980,"last":3980},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}