Using master games statistics on the squares played
説明
Most state-of the art Shogi programs adopt variants of the fixed-depth alpha-beta search algorithm. However, there are numerous search extensions that explore "interesting" lines of play more deeply. Most search extensions make the decision to extend a certain line of play dynamically. We propose a static topological frequency based search extension. That is, the decision to extend searching of a certain move is dependant on the frequency the relevant square was played in master games. As this method was inspired by and akin to Realization Probability Search we named it Topological Frequency Bias (TFB). The proposed TFB has been incorporated to our computer Shogi program, TACOS, and two experiments proved its effectiveness.
Most state-of the art Shogi programs adopt variants of the fixed-depth alpha-beta search algorithm. However, there are numerous search extensions that explore "interesting" lines of play more deeply. Most search extensions make the decision to extend a certain line of play dynamically. We propose a static topological frequency based search extension. That is, the decision to extend searching of a certain move is dependant on the frequency the relevant square was played in master games. As this method was inspired by and akin to Realization Probability Search we named it Topological Frequency Bias (TFB). The proposed TFB has been incorporated to our computer Shogi program, TACOS, and two experiments proved its effectiveness.
収録刊行物
-
- ゲームプログラミングワークショップ2004論文集
-
ゲームプログラミングワークショップ2004論文集 2004 100-103, 2004-11-12
情報処理学会
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1050574047131068672
-
- NII論文ID
- 170000080222
-
- 本文言語コード
- en
-
- 資料種別
- conference paper
-
- データソース種別
-
- IRDB
- CiNii Articles