摘要: Recently, a methodology has been proposed for boosting the computational intelligence of randomized game-playing programs. We modify this by working on rectangular, rather than square, matrices; and we apply it to Domineering game. At CIG 2015, propose demo in case Go. Hence, players site can contribute scientific validation playing (in double blind manner) against both original algorithm its boosted version.
sci-hub.se 参考文章(3)
Romaric Gaudel, Jean-Baptiste Hoock, Julien Pérez, Nataliya Sokolovska, Olivier Teytaud, Principled method for exploiting opening books annual conference on computers. ,vol. 6515, pp. 136- 144 ,(2010) , 10.1007/978-3-642-17928-0_13
David L. St-Pierre, Olivier Teytaud, The Nash and the bandit approaches for adversarial portfolios computational intelligence and games. pp. 1- 7 ,(2014) , 10.1109/CIG.2014.6932897
Leandro Soriano Marcolino, Milind Tambe, Vaishnavh Nagarajan, Every team deserves a second chance: identifying when things go wrong (student abstract version) national conference on artificial intelligence. pp. 4184- 4185 ,(2015)