Feature extraction from skilled player's logs in PuyoPuyo

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  • ぷよぷよにおける人間のプレイデータの特徴量抽出
  • プヨプ ヨニ オケル ニンゲン ノ プレイデータ ノ トクチョウリョウ チュウシュツ

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The techniques of artificial intelligence (AI) have been rapidly developing in video games. One of the main aims of AI implementation is to win against the human players. This is already achieved in some games, such as chess and shogi. Nowadays, the interest is moved to enhance the enjoyment of the players. Many researches are devoted to develop a human-like AI player to entertain human player. In this paper, we focused on a video game named PuyoPuyo. PuyoPuyo is one of the tile-matchins puzzle game controlling two pair of falling blocks. Random distribution of the blocks makes it difficult to set them into the ideal pattern. Skilled player seems to have some ideal pattern template models in their mind. This paper tried to derive these templates from the placements of blocks stacked by the skilled human player. Using these templates, it is partially capable of reconstruction the player's placements.

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