{"type":"ScholarlyArticle","title":"Accelerating Best Response Calculation in Large Extensive Games","authors":[{"name":"Michael Johanson","slug":"michael-johanson","given":"Michael","family":"Johanson","affiliation":""},{"name":"Kevin Waugh","slug":"kevin-waugh","given":"Kevin","family":"Waugh","affiliation":""},{"name":"Michael H. Bowling","slug":"michael-h-bowling","given":"Michael H.","family":"Bowling","affiliation":""},{"name":"Martin Zinkevich","slug":"martin-zinkevich","given":"Martin","family":"Zinkevich","affiliation":""}],"abstract":"One fundamental evaluation criteria of an AI technique is its performance in the worst-case. For static strategies in extensive games, this can be computed using a best response computation. Conventionally, this requires a full game tree traversal. For very large games, such as poker, that traversal is infeasible to perform on modern hardware. In this paper, we detail a general technique for best response computations that can often avoid a full game tree traversal. Additionally, our method is specifically well-suited for parallel environments. We apply this approach to computing the worst-case performance of a number of strategies in heads-up limit Texas hold'em, which, prior to this work, was not possible. We explore these results thoroughly as they provide insight into the effects of abstraction on worst-case performance in large imperfect information games. This is a topic that has received much attention, but could not previously be examined outside of toy domains.","doi":"10.5591/978-1-57735-516-8/IJCAI11-054","url":"https://ijcai.org/proceedings/2011/54","pdf":"https://ijcai.org/proceedings/2011/0054.pdf","markdown":"https://ijcai.org/proceedings/2011/54.md","bibtex":"https://ijcai.org/proceedings/2011/bibtex/54","volume":{"slug":"2011","title":"Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2011","url":"https://ijcai.org/proceedings/2011/","year":2011,"location":"Barcelona, Catalonia, Spain","dates":"16–22 July 2011","editors":"Toby Walsh","isbn":"978-1-57735-512-0; 978-1-57735-513-7; 978-1-57735-514-4; 978-1-57735-515-1; 978-1-57735-516-8","publisher":"AAAI Press/International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":54,"pages":{"first":258,"last":264},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}