用地标、纪念碑和灯塔三类概念，让机器更好理解游戏生成内容的体验价值。
Landmarks, Monuments, and Beacons: Understanding Generative Calls to Action
- 从玩家视角定义三类生成内容特征：可见性、感染力与行动号召。
- 可借助现有技术自动识别并评估这些特征，实现内容组件的自动化分解。
- 适用于多种游戏类型，促进人文与技术研究融合。
程序化生成内容（PCG）的算法评估难以匹配人类体验，尤其针对复合型作品。自动分解作为一种可能解决方案，需要满足多重属性的概念支撑。基于游戏研究与游戏人工智能，本文提出嵌套概念：地标（Landmarks）、纪念碑（Monuments）和灯塔（Beacons）。这三者均从玩家中心出发，分别体现内容的可感知性、情感唤起性与行动引导性。这些概念通用性强，适用于各类游戏。我们论证其可通过当前科研与工业界常用技术进行发现与评估，为实现全自动化PCG分解及关键子组件评价提供路径。尽管本文聚焦混合主动性与组合式PCG，但认为其适用范围更广。本方法旨在连接人文学科与技术游戏研究，推动更有效的计算化PCG评估。
原文摘要 · Abstract (English)
Algorithmic evaluation of procedurally generated content struggles to find metrics that align with human experience, particularly for composite artefacts. Automatic decomposition as a possible solution requires concepts that meet a range of properties. To this end, drawing on Games Studies and Game AI research, we introduce the nested concepts of \textit{Landmarks}, \textit{Monuments}, and \textit{Beacons}. These concepts are based on the artefact's perceivability, evocativeness, and Call to Action, all from a player-centric perspective. These terms are generic to games and usable across genres. We argue that these entities can be found and evaluated with techniques currently used in both research and industry, opening a path towards a fully automated decomposition of PCG, and evaluation of the salient sub-components. Although the work presented here emphasises mixed-initiative PCG and compositional PCG, we believe it applies beyond those domains. With this approach, we intend to create a connection between humanities and technical game research and allow for better computational PCG evaluation
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