The Confidence Intervals in Computer Go

Leszek Śliwa


The confidence intervals in computer Go are used in MCTS algorithm to select the potentially most promising moves that should be evaluated with Monte-Carlo simulations. Smart selection of moves for evaluation has the crucial impact on program’s playing strength. This paper describes the application of confidence intervals for binomial distributed random variables in computer Go. In practice, the estimation of confidence intervals of binomial distribution is difficult and computationally exhausted. Now due to computer technology progress and functions offered by many libraries calculation of confidence intervals for discreet, binomial distribution become an easy task. This research shows that the move-selection strategy which implements calculation of the exact confidence intervals based on discreet, binomial distribution is much more effective than based on normal. The new approach shows its advantages particularly in games played on medium and large boards.
Author Leszek Śliwa II
Leszek Śliwa,,
- The Institute of Computer Science
Publication size in sheets0.55
Book Rutkowski Leszek, Korytkowski Marcin, Scherer Rafal, Tadeusiewicz Ryszard, Zadeh Lotfi A., Zurada Jacek (eds.): Artificial Intelligence and Soft Computing, 15th International Conference, ICAISC 2016, Proceedings, Part II, Lecture Notes in Artificial Intelligence, vol. 9693, no. 1, 2016, Springer International Publishing, ISBN 978-3-319-39383-4, [978-3-319-39384-1], 770 p., DOI:10.1007/978-3-319-39384-1
Keywords in EnglishComputer Go, AI, MCTS, UCT, Confidence intervals, Binomial distribution
projectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 18-05-2015, end date 30-11-2016, II/2015/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
Score (nominal)15
ScoreMinisterial score = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
Ministerial score (2013-2016) = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
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