@techreport{oai:ipsj.ixsq.nii.ac.jp:00142570,
 author = {大森, 翔太朗 and 金子, 知適 and Shotaro, Omori and Tomoyuki, Kaneko},
 issue = {6},
 month = {Jun},
 note = {近年プレイヤの個性に関する研究が人工知能の分野で取り組まれ始めている．本研究では，将棋の指し手の選択に注目し，コンピュータプログラムで棋風を実現する方法について提案する．棋風としては，プレイヤが攻めや受けなど特徴を持つ指し手を選ぶ傾向についてに着目する．棋風を統計的に分析した過去の研究を参考に攻めの特徴と受けの特徴を決め，攻めと受けの棋風について，それぞれの特徴の現れているプレイヤの棋譜を選別する．そしてそれらの棋譜を教師に評価関数の機械学習を行う．提案手法で学習したプログラムと，一般の棋譜で学習したプログラムの差を，攻めと受けに関する次の一手問題を題材に評価する予定である．, There are several work on playing styles of computer players in Artificial Intelligence research in recent years. This study proposes a method to make a computer player have an intended playing style in shogi. We focus on how a player prefers attack or defense moves as an example of a playing style, because many moves in shogi are categorized in attack or defense. We select a set of game records played by players having the intended playing style, based on statistical analysis proposed in existing researches. Then, we conduct a supervised learning of an evaluation function by using the records. The effectiveness of our method will be measured in our experiments. We will prepare test positions for attack and defense moves in shogi, and compare how well programs with or without the tuning of evaluation functions solves the test positions.},
 title = {機械学習を用いた将棋における棋風の学習の研究},
 year = {2015}
}