创意游戏：面向机制感知的创意游戏生成

摘要

大型语言模型能够生成看似合理的游戏代码，但将这种能力转化为迭代式创意提升仍面临挑战。实践中，单次生成往往会产生脆弱的运行时行为、版本间经验积累薄弱，以及过于主观而难以作为可靠优化指标的创意评分。另一个局限在于游戏机制常被视作事后描述，而非生成过程中可规划、追踪、保存和评估的显式对象。本报告提出CreativeGame——一个面向迭代式HTML5游戏生成的多智能体系统，通过四个耦合理念解决上述问题：以程序化信号而非纯LLM判断为核心的代理奖励机制；支持跨版本经验积累的谱系限定记忆；融入程序修复与奖励机制的运行时验证；以及机制引导的规划循环，即在代码生成前将检索到的机制知识转化为显式机制方案。该系统的目标不仅是单步生成可运行成品，更要支持可解释的版本间演进。当前系统包含71个存储谱系、88个存档节点及拥有774条记录的全局机制库，通过6,181行Python代码实现并配备检测与可视化工具。因此该系统具备足够规模以支持架构分析、奖励机制检视和真实谱系级案例研究，而非仅停留在提示层面的演示。一个真实的四代谱系案例表明，机制级创新可在后续版本中涌现，并能通过版本间记录直接观测。因此核心贡献不仅在于游戏生成，更在于通过显式机制变化观测渐进式演进的具体流程。

English

Large language models can generate plausible game code, but turning this capability into iterative creative improvement remains difficult. In practice, single-shot generation often produces brittle runtime behavior, weak accumulation of experience across versions, and creativity scores that are too subjective to serve as reliable optimization signals. A further limitation is that mechanics are frequently treated only as post-hoc descriptions, rather than as explicit objects that can be planned, tracked, preserved, and evaluated during generation. This report presents CreativeGame, a multi-agent system for iterative HTML5 game generation that addresses these issues through four coupled ideas: a proxy reward centered on programmatic signals rather than pure LLM judgment; lineage-scoped memory for cross-version experience accumulation; runtime validation integrated into both repair and reward; and a mechanic-guided planning loop in which retrieved mechanic knowledge is converted into an explicit mechanic plan before code generation begins. The goal is not merely to produce a playable artifact in one step, but to support interpretable version-to-version evolution. The current system contains 71 stored lineages, 88 saved nodes, and a 774-entry global mechanic archive, implemented in 6{,}181 lines of Python together with inspection and visualization tooling. The system is therefore substantial enough to support architectural analysis, reward inspection, and real lineage-level case studies rather than only prompt-level demos. A real 4-generation lineage shows that mechanic-level innovation can emerge in later versions and can be inspected directly through version-to-version records. The central contribution is therefore not only game generation, but a concrete pipeline for observing progressive evolution through explicit mechanic change.

创意游戏：面向机制感知的创意游戏生成

CreativeGame:Toward Mechanic-Aware Creative Game Generation

摘要

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