Inferring and Comparing Game Difficulty Curves using Player-vs-Level Match Data.

Anurag Sarkar, Seth Cooper
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引用次数: 5

Abstract

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.

Abstract Image

Abstract Image

使用玩家vs关卡匹配数据推断和比较游戏难度曲线。
先前的工作主要集中在通过使用函数组合来给出曲线及其转换的精确定义来形式化难度曲线。然而,所提出的框架是使用单个游戏来演示的,并且曲线和转换是根据基于游戏评级的动态难度系统来定义的。在这项工作中,我们使用一种基于上述难度系统的方法从游戏玩法数据中推断出难度曲线,但这种方法也可以推广到其他游戏中,因为这些游戏可以获得玩家对玩家级别的输赢结果信息。此外,由于这种方法使用了与过去相同的难度机制,它让我们能够同样地利用功能组合来比较不同游戏的难度曲线,即使用明确定义的词汇,使用固定或动态的关卡顺序。我们使用四种不同的游戏来演示我们的方法,该方法依赖于对传统的基于评级的比赛数据回放的调整,我们也在这项工作中展示了这一点。
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