AI原生游戏：综述与路线图
AI Native Games: A Survey and Roadmap
AI总结：
本文定义AI原生游戏为运行时生成式AI构成核心循环的游戏，提出G/N分类法分析53个实例，指出核心设计问题是将语义开放性组织为稳定游戏玩法，并给出路线图。
摘要：
生成式AI现在使游戏能够在运行时生成对话、任务、角色、图像和世界。然而，仅靠生成并不能使游戏成为AI原生，也不能保证可玩性。本文通过运行时生成式AI是否构成核心循环来定义AI原生游戏：如果移除或简单替换AI组件，核心玩法将崩溃或发生根本性变化。这个反事实标准将AI原生游戏与AI增强游戏、边界制品、聊天机器人、酒馆风格角色扮演、程序化内容生成和AI辅助制作区分开来。使用这一定义，我们筛选候选制品并分析了53个公开可用的AI原生游戏和原型。我们引入了一个双轴G/N分类法：G轴捕捉面向玩家的游戏类型，而N轴捕捉使生成式AI对游戏不可或缺的主导AI机制。语料库集中在以语言为中心的设计上，尤其是叙事冒险、认知交互和生成叙事，而语义裁决、多智能体模拟、生成式构建和关系/同伴游戏等类别则较少出现。我们认为核心设计问题是将语义开放性组织为稳定的游戏玩法。AI原生设计依赖于机械不变量：目标、规则、状态、反馈、节奏和玩家能动性，这些使开放的AI输出可解释且具有后果。最后，我们给出了可控生成、AI作为机制设计、多模态和多智能体系统、推理经济学、评估、安全与监管的路线图。
英文摘要：
Generative AI now enables games to produce dialogue, quests, characters, images, and worlds at runtime. Yet generation alone does not make a game AI-native, nor does it guarantee playability. This paper defines AI-native games by whether runtime generative AI is constitutive of the core loop: if the AI component were removed or trivially replaced, the central form of play would collapse or become fundamentally different. This counterfactual criterion separates AI-native games from AI-augmented games and adjacent boundary artifacts. Using this definition, we screen candidate artifacts and analyze 53 publicly available AI-native games and prototypes. We introduce a dual-axis G/N taxonomy: the G-axis captures player-facing game type, while the N-axis captures the dominant AI mechanic that makes generative AI indispensable to play. The corpus is concentrated around language-forward designs, especially narrative adventure, epistemic interaction, and generative narrative, while categories such as semantic adjudication, multi-agent simulation, generative construction, and relationship/companion play remain less represented. We argue that the central design problem is organizing semantic openness into stable gameplay. AI-native design depends on mechanical invariants: goals, rules, state, feedback, pacing, and player agency that make open-ended AI outputs interpretable and consequential. We conclude with a roadmap for controllable generation, AI-as-mechanic design, multimodal and multi-agent systems, inference economics, evaluation, safety, and regulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
