Inferring and Comparing Game Difficulty Curves using Player-vs-Level Match Data.
Inferring and Comparing Game Difficulty Curves using Player-vs-Level Match Data.
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使用玩家与级别的匹配数据推断和比较游戏难度曲线。
DOI：
10.1109/cig.2019.8848102
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Cooper,Seth
中科院分区：
文献类型：
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作者：
Sarkar,Anurag;Cooper,Seth
以前的工作集中于通过使用函数组合来给出曲线及其变换的精确定义来形式化难度曲线。然而，建议的框架是使用单个游戏演示的，曲线和转换是相对于游戏的基于评级的动态难度系统定义的。在这项工作中，我们使用一种基于前述难度系统的方法从游戏数据中推断难度曲线，但这种方法也可以推广到其他可以获得玩家对级别输赢结果信息的游戏。此外，由于此方法使用与过去工作相同的难度机制，因此它允许我们类似地利用函数组合来比较具有固定或动态级别排序的游戏的难度曲线，使用明确定义的词汇。我们使用四个不同的游戏来演示我们的方法，它依赖于对基于评级的比赛数据的传统回放的调整，我们在本工作中也提出了这一点。
Prior work has focused on formalizing difficulty curves by using function composition to give precise definitions to curves and their transformations. However, the proposed framework was demonstrated using a single game, and the curves and transformations were defined with respect to the game’s ratings-based dynamic difficulty system. In this work, we infer difficulty curves from gameplay data using a method that is based on the aforementioned difficulty system but that can also be generalized to other games for which information on player-vs-level win/loss outcomes is available. Moreover, since this method uses the same difficulty mechanism as past work, it lets us similarly leverage function composition to compare difficulty curves across games, having either a fixed or dynamic level ordering, using a clearly defined vocabulary. We use four different games to demonstrate our method, which relies on an adjustment to traditional playback of ratings-based match data, which we also present in this work.