AI 正在接管游戏的全生命周期，但每个环节都还各玩各的
我们习惯把 AI 在游戏里的角色想成「会打游戏的对手」。这篇综述把近年的研究摊开，发现 AI 已经渗透进游戏从设计、开发、运行到测试的每一个环节：有的 AI 在建模玩家行为，有的在自动生成关卡，有的在运行时动态调整难度，有的在帮你测 bug。但问题在于，这些方向各自为政——一个 AI 在《星际争霸》里学会的操控方式，换到《我的世界》就完全失效；一个能生成关卡的系统，它的输出也没法直接喂给另一个负责测试的系统。研究者把文献按 AI 输出的用途分成六个角色，发现真正能跨场景迁移的只有少数抽象能力(比如用对局轨迹训练世界模型)，而控制方式、游戏规则、引擎接口这些底层结构几乎都是绑死的。换句话说，AI 在游戏里正在从「单点突破」走向「全面开花」，但离「一个通用游戏 AI」还差着十万八千里。这不是你明天能玩到的功能，但它告诉你：未来游戏里的 AI 会越来越多，而且它们之间的协作，才是真正的战场。
📄 原文摘要(英文)
Foundation models, alongside advances in learned game-world models, are reshaping AI across the game lifecycle. Beyond playing games, recent systems model players and game dynamics, support design and development, adapt player-facing experiences at runtime, and evaluate resulting artifacts. Yet these directions have evolved largely separately, obscuring which capabilities transfer across settings and which remain tied to particular games, engines, interfaces, or player populations. We organize the literature into six roles according to the immediate use of AI output: playing and acting; modeling players and games; designing games; building and maintaining games; generating and adapting at runtime; and testing and evaluating games. For each role, we examine what structure is supplied by the game or workflow, what AI learns or produces, which capabilities and artifacts transfer across settings and roles, and what evidence supports the claims. We identify cross-role connections: trajectories train world models, learned environments provide experience for agents, design specifications drive executable implementations, and play or testing feedback guides revision. However, control schemes, rules, engine interfaces, state representations, and player contexts often remain setting-specific, so downstream claims require validation in the target setting. Evaluation is most standardized for bounded game playing and selected learned environments, while persistent state in learned worlds, repeated software revision, validated player modeling, sustained runtime adaptation, and representative automated testing remain less established. The central challenge is to reuse or transfer outputs and capabilities across roles while re-establishing evidence for effectiveness in the game-specific contexts where they are used.