{"type":"ScholarlyArticle","title":"Corpus-based, Statistical Goal Recognition","authors":[{"name":"Nate Blaylock","slug":"nate-blaylock","given":"Nate","family":"Blaylock","affiliation":""},{"name":"James F. Allen","slug":"james-f-allen","given":"James F.","family":"Allen","affiliation":""}],"abstract":"Goal recognition for dialogue systems needs to be fast, make early predictions, and be portable. We present initial work which shows that using statistical, corpus-based methods to build goal recognizers may be a viable way to meet those needs. Our goal recognizer is trained on data from a plan corpus and then used to determine the agent's most likely goal based on that data. The algorithm is linear in the number of goals, and performs very well in terms of accuracy and early prediction. In addition, it is more easily portable to new domains as does not require a hand-crafted plan library.","doi":null,"url":"https://ijcai.org/proceedings/2003/185","pdf":"https://ijcai.org/proceedings/2003/0185.pdf","markdown":"https://ijcai.org/proceedings/2003/185.md","bibtex":"https://ijcai.org/proceedings/2003/bibtex/185","volume":{"slug":"2003","title":"Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2003","url":"https://ijcai.org/proceedings/2003/","year":2003,"location":"Acapulco, Mexico","dates":"","editors":"Georg Gottlob","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":185,"pages":{"first":1303,"last":1307},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}