{"type":"ScholarlyArticle","title":"Optimal Searches From AND and OR Nodes","authors":[{"name":"Jeffrey A. Barnett","slug":"jeffrey-a-barnett","given":"Jeffrey A.","family":"Barnett","affiliation":"USC Information Sciences Institute 4676 Admiralty Way Marina del Rey , California 90291"}],"abstract":"The problem is to organize search from an AND node in a way thatminimizes expected cost. The result is derived as a corollary toea rlier work of Simon and Kadane. It is shown that, unless knowledge gained during the search changes the probability or cost estimates of remaining parts of the search, the original a priori strategy remains optimal. The effect of approximating the searc h statistics used to determine the optimal strategy is examined , and it is found that the impact on expected cost is linearly bounded by the quality of the approximation . Then the case of searching an infinite conjunct is considered. Finally, some related research top ics are discussed.","doi":null,"url":"https://ijcai.org/proceedings/1983/191","pdf":"https://ijcai.org/proceedings/1983/0191.pdf","markdown":"https://ijcai.org/proceedings/1983/191.md","bibtex":"https://ijcai.org/proceedings/1983/bibtex/191","volume":{"slug":"1983","title":"Proceedings of the Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1983","url":"https://ijcai.org/proceedings/1983/","year":1983,"location":"Karlsruhe, West Germany","dates":"","editors":"Alan Bundy","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Planning and Search","track":"Planning and Search","number":191,"pages":{"first":786,"last":787},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}