@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00240735,
 author = {窪木, 響大 and シュエ, ジュウシュエン and 池田, 心 and Kyota, Kuboki and Chu-Hsuan, Hsueh and Kokolo, Ikeda},
 book = {ゲームプログラミングワークショップ2024論文集},
 month = {Nov},
 note = {近年ではゲーム AI を用いて人を楽しませたり指導する研究が進められている．そういった中で，プレイヤの棋力を正確に推定することは，適切な対戦相手 AI の用意やプレイヤの実力向上のためのフィードバックなどに活用できる．チェスや将棋，囲碁においては強いゲーム AI の最善手とプレイヤの着手の評価値の差分「損失」を使った棋力推定が行われている．しかし，損失はゲームの展開に大きく影響されてしまい，少ない棋譜では推定結果がばらついてしまうという課題がある．本研究ではそういったゲームの展開による過度な影響を抑制した指標の作成方法を提案する．具体的には，連続して損失が高い手が出た場合にその一部をカウントしない，ばらつきの大きい試合後半を見ない，展開に影響されにくい「形の良さ」を見る，といった工夫を行った．これをもとに少数棋譜に対して棋力推定を行い，提案手法によって棋力の推定結果の標準偏差を 0.387 としつつ精度を RMSE 0.752 とすることができた．, In recent years, researchers has used game AI to entertain and teach human players. In this context, accurate estimation of players’ strength is crucial for preparing appropriate opponent AIs and providing feedback for skill improvement. In chess, shogi, and Go, researchers have used the metric "loss," which is the difference in evaluation values between strong game AI' s best move and the player’ s move, to estimate players’ strength. However, there is a problem that such losses can be very much influenced by game progresses, and the results of players’ strength estimation vary with a small number of game records. In this paper, we proposed methods for calculating strength evaluation metrics that reduce excessive influence from game progresses. Specifically, we applied the following methods: not counting some high-loss moves when they occur consecutively, not using the second half of the game, which has a large variation , and using the metric ”goodness of shape”, which is less influenced by game progresses. We applied filters to the calculation, such as not counting some high-loss moves when they occur consecutively. Based on this, we estimated players’ strength using a small number of game records. As a result, we succeeded in achieving a standard deviation of 0.387 and RMSE 0.752 using our porposed methods.},
 pages = {117--124},
 publisher = {情報処理学会},
 title = {ゲームの展開に過度に影響されないプレイヤ強さの推定方法},
 volume = {2024},
 year = {2024}
}