Decision Tree Analysis in Game Informatics
Decision Tree Analysis in Game Informatics
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DOI：
10.1007/978-3-319-64051-8_2
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发表时间：
2017-07
期刊：
影响因子：
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通讯作者：
Masatoshi A. Konishi;Seiya Okubo;T. Nishino;Mitsuo Wakatsuki
中科院分区：
文献类型：
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作者：
Masatoshi A. Konishi;Seiya Okubo;T. Nishino;Mitsuo Wakatsuki
电脑大兴慜是用玩家程序玩日本流行的纸牌游戏“大兴慜”。由于计算机大兴民的强大棋手程序使用了机器学习技术，例如蒙特卡洛方法，因此很难预测程序的行为。在本研究中，我们通过决策树分析来提取玩家程序的特征。通过基于三种视点生成决策树来提取程序的特征。为了证明该方法的有效性，进行了计算机实验。我们将我们的方法应用到三个行为比较明显的程序中，通过观察程序的真实行为来证实提取的特征是正确的。
Computer Daihinmin involves playing Daihinmin, a popular card game in Japan, by using a player program. Because strong player programs of Computer Daihinmin use machine-learning techniques, such as the Monte Carlo method, predicting the program’s behavior is difficult. In this study, we extract the features of the player program through decision tree analysis. The features of programs are extracted by generating decision trees based on three types of viewpoints. To show the validity of our method, computer experiments were conducted. We applied our method to three programs with relatively obvious behaviors, and we confirmed that the extracted features were correct by observing real behaviors of the programs.