@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00091372,
 author = {西村, 友伸 and 大用, 庫智 and 高橋, 達二 and Tomonobu, Nishimura and Kuratomo, Oyo and Tatsuji, Takahashi},
 book = {ゲームプログラミングワークショップ2012論文集},
 issue = {6},
 month = {Nov},
 note = {本研究では甲野により提案された可変参照型緩対称推論をモンテカルロ木探索に応用させ，その効果を測る為にリバーシのAI に実装し，モンテカルロ木探索で広く利用されているUCT を実装したAI と対戦させた．その結果ある程度のプレイアウトの上ではUCT に勝ち越し，可変参照が木探索においても有効に作用することが分かった．, This study Was applied to the Monte Carlo tree search to loosely symmetric reasoning proposed with variable reference by Khono. In order to measure the effect of the variable reference, to play against UTC in Reversi. As a result, it was found that on a certain amount of playout is stronger than UCT, the variable reference works effectively even in the tree search.},
 pages = {191--196},
 publisher = {情報処理学会},
 title = {可変参照型緩対称性推論のモンテカルロ木探索での効果},
 volume = {2012},
 year = {2012}
}