@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00229343,
 author = {杵渕, 哲彦 and 伊藤, 毅志 and Tetsuhiko, Kinebuchi and Takeshi, Ito},
 book = {ゲームプログラミングワークショップ2023論文集},
 month = {Nov},
 note = {ゲームAI はこれまで強さの向上を目的として発展してきたが，近年は人間の程よい対戦相手となるなど強さ以外の研究も行われており，その一つとして人間の選択結果を予測することが挙げられる．本研究では将棋を題材にあまり強くない人間の指し手を模倣することを目的とし，MCTS の探索傾向を変化させて目的の強さのプレイヤが行うような探索に近づけることで，一致率の向上を試みた．既存の探索を全く行わない手法では予測出来ない指し手を予測できたが，既存手法と比較して一致率は下回った．, Game AI has been developed for the purpose of improving strength, but recently there has been some research done outside of strength, such as being just the right opponent. This research aim to imitate human player’s move in Shogi. By changing the search tendency of MCTS to imitate the search conducted by human players, we attempted to improve move-matching accuracy. The proposed method was able to predict moves that could not be predicted by the existing method, but move-matching accuracy was lower than that of the existing method.},
 pages = {56--58},
 publisher = {情報処理学会},
 title = {モンテカルロ木探索のパラメータ調整による人間の指し手との一致率の向上},
 volume = {2023},
 year = {2023}
}