Game economies (GEs) describe how resources in games are created, transformed, or exchanged: They underpin most games and exist in different complexities. Their complexity may directly impact player difficulty. Nevertheless, neither difficulty nor complexity adjustment has been explored for GEs. Moreover, there is a lack of knowledge about complexity in GEs, how to define or assess it, and how it can be employed by automated adjustment approaches in game development to target specific complexity. We present a proof-of-concept for using evolutionary algorithms to craft targeted complexity graphs to model GEs. In a technical evaluation, we tested our first working definition of complexity in GEs. We then evaluated player-perceived complexity in a city-building game prototype through a user study and confirmed the generated GEs' complexity in an online survey. Our approach toward reliably creating GEs of specific complexity can facilitate game development and player testing but also inform and ground research on player perception of GE complexity.

中文翻译：

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使用进化算法来确定游戏经济中的复杂程度

游戏经济 (GE) 描述了游戏中的资源是如何创建、转换或交换的：它们支撑着大多数游戏，并以不同的复杂性存在。它们的复杂性可能会直接影响玩家的难度。然而，对于 GE，既没有探索难度也没有调整复杂性。此外，缺乏关于 GE 复杂性的知识，如何定义或评估它，以及如何通过游戏开发中的自动调整方法来使用它来针对特定的复杂性。我们提出了使用进化算法制作目标复杂度图来模拟 GE 的概念验证。在技​​术评估中，我们测试了我们对 GE 复杂性的第一个工作定义。然后，我们通过用户研究评估了玩家在城市建设游戏原型中的感知复杂性，并确认了生成的 GEs' 在线调查的复杂性。我们可靠地创建具有特定复杂性的 GE 的方法可以促进游戏开发和玩家测试，但也可以为玩家对 GE 复杂性的感知提供信息和基础研究。