{"type":"ScholarlyArticle","title":"Decision Generalisation from Game Logs in No Limit Texas Hold'em","authors":[{"name":"Jonathan Rubin","slug":"jonathan-rubin","given":"Jonathan","family":"Rubin","affiliation":""},{"name":"Ian D. Watson","slug":"ian-d-watson","given":"Ian D.","family":"Watson","affiliation":""}],"abstract":"Given a set of data, recorded by observing the decisions of an expert player, we present a case-based framework that allows the successful generalisation of those decisions in the game of no limit Texas Hold'em. We address the problems of determining a suitable action abstraction and the resulting state translation that is required to map real-value bet amounts into a discrete set of abstract actions. We also detail the similarity metrics used in order to identify similar scenarios, without which no generalisation of playing decisions would be possible. We show that we were able to successfully generalise no limit betting decisions from recorded data via our agent, SartreNL, which achieved a 5th place finish out of 11 opponents at the 2012 Annual Computer Poker Competition.","doi":null,"url":"https://ijcai.org/proceedings/2013/457","pdf":"https://ijcai.org/proceedings/2013/0457.pdf","markdown":"https://ijcai.org/proceedings/2013/457.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/457","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":457,"pages":{"first":3062,"last":3065},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}