{"type":"ScholarlyArticle","title":"Depth-bounded Discrepancy Search","authors":[{"name":"Toby Walsh","slug":"toby-walsh","given":"Toby","family":"Walsh","affiliation":""}],"abstract":"Many search trees are impractically large to explore exhaustivel y. Recently, techniques like limited discrepancy search have been proposed for improving the chance of finding a goal in a limited amount of search. Depth-bound ed discrepancy search offers such a hop e. The motivation behind depth-bounded discrepancy search is that branching heuristics are more likely to be wrong at the top of the tree than at the bottom . We therefore combine one of the best features of limited discrepancy search - the ability to undo early mistakes - with the completeness of iterative deepening search. We show theoretically and experimentally that this novel combination outperforms existing techniques.","doi":null,"url":"https://ijcai.org/proceedings/1997/200","pdf":"https://ijcai.org/proceedings/1997/0200.pdf","markdown":"https://ijcai.org/proceedings/1997/200.md","bibtex":"https://ijcai.org/proceedings/1997/bibtex/200","volume":{"slug":"1997","title":"Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1997","url":"https://ijcai.org/proceedings/1997/","year":1997,"location":"Nagoya, Japan","dates":"","editors":"Martha E. Pollack","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Search","track":"Search","number":200,"pages":{"first":1388,"last":1394},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}