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首页> 外文期刊>International journal of computer games technology >Visualizing Changes in Strategy Use across Attempts via State Diagrams: A Case Study
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Visualizing Changes in Strategy Use across Attempts via State Diagrams: A Case Study

机译：通过状态图可视化各种尝试中策略使用的变化：一个案例研究

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Game log data have great potential to provide actionable information about the in-game behavior of players. However, these low-level behavioral data are notoriously difficult to analyze due to the challenges associated with extracting meaning from sparse data stored at such a small grain size. This paper describes a three-step solution that uses cluster analysis to determine which strategies players use to solve levels in the game, sequence mining to identify changes in strategy across multiple attempts at the same level, and state transition diagrams to visualize the strategy sequences identified by the sequence mining. In the educational video game used in this case study, cluster analysis successfully identified 15 different in-game strategies. The sequence mining found an average of 40 different sequences of strategy use per level, which the state transition diagrams successfully displayed in an interpretable way.
机译：游戏日志数据具有提供有关玩家游戏中行为的可操作信息的巨大潜力。然而，由于与从以如此小的粒度存储的稀疏数据中提取含义相关的挑战，众所周知，这些低级行为数据难以分析。本文介绍了一个三步解决方案，该解决方案使用聚类分析来确定玩家用来解决游戏中各个关卡的策略，序列挖掘以识别同一级别的多次尝试中策略的变化，以及状态转移图以可视化所标识的策略序列通过序列挖掘。在本案例研究中使用的教育视频游戏中，聚类分析成功地确定了15种不同的游戏策略。序列挖掘发现每个级别平均使用40种不同的策略序列，状态转换图以一种可解释的方式成功显示了这些序列。

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