@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00095827,
 author = {齋藤, 晃介 and 三輪, 誠 and 鶴岡, 慶雅 and 近山, 隆 and Kosuke, Saito and Makoto, Miwa and Yoshimasa, Tsuruoka and Takashi, Chikayama},
 book = {ゲームプログラミングワークショップ2013論文集},
 month = {Nov},
 note = {ランダム性を持つゲームでは，プレイヤーが未来に得る情報が確率的に決まる．そのようなゲームの中から，ぷよぷよという落下型パズルゲームに着目する．ぷよぷよは，人間のプレイヤーは将来の完成型を考えて行動を選択しており，また完全にランダムな探索が無駄になりやすいために先読みが難しいゲームである．本論文では，確定完全情報パズルゲームで有効性を示されたNested Monte-Carlo Searchをぷよぷよに適用する手法を提案し，そのアルゴリズムの振る舞いを調査した．その結果，今回の設定では計算時間に見合うだけの有意な性能は示せなかった．, Indeterminate games are games in which outcome of plays has probabilistic nature. Among such games, we focus on Puyo-puyo, which is a popular tile-matching video game. Puyo-puyo is a difficult game, because human players determine each action in such a way that it will lead to a good completed form in the future and a completely random search often comes out to be wasteful. In this paper, we propose a method for applying Nested Monte-Carlo Search, the effectiveness of which has been shown in logical perfect information games, to Puyo-puyo and investigate its behavior. As a result, we can not show the efficiency which reflects time to calculate.},
 pages = {134--137},
 publisher = {情報処理学会},
 title = {Nested Monte Carlo Searchのぷよぷよへの適用},
 year = {2013}
}