{"type":"ScholarlyArticle","title":"Mining Expert Play to Guide Monte Carlo Search in the Opening Moves of Go","authors":[{"name":"Erik S. Steinmetz","slug":"erik-s-steinmetz","given":"Erik S.","family":"Steinmetz","affiliation":""},{"name":"Maria L. Gini","slug":"maria-l-gini","given":"Maria L.","family":"Gini","affiliation":""}],"abstract":"We propose a method to guide a Monte Carlo search in the initial moves of the game of Go. Our method matches the current state of a Go board against clusters of board configurations that are derived from a large number of games played by experts. The main advantage of this method is that it does not require an exact match of the current board, and hence is effective for a longer sequence of moves compared to traditional opening books. We apply this method to two different open-source Go-playing programs. Our experiments show that this method, through its filtering or biasing the choice of a next move to a small subset of possible moves, improves play effectively in the initial moves of a game.","doi":null,"url":"https://ijcai.org/proceedings/2015/118","pdf":"https://ijcai.org/proceedings/2015/0118.pdf","markdown":"https://ijcai.org/proceedings/2015/118.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/118","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Heuristic Search","track":"Main Track","number":118,"pages":{"first":801,"last":806},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}