arXiv：cs.AI· Yixu Huang, Bo Li, Na Li, Zhe Wang, Kaijie Chen, Haonan Ge, Qingyi Si, Yuanzhe Shen, Ruihan Yang, Guangjing Wang, Hongcheng Guo·· 4 小时前AI 评分38
用 GUI 智能体实现持续游戏生成：PlaytestArena 与 Play2Code
GUI Agents for Continual Game Generation
AI 导读
研究者提出 PlaytestArena 评测环境和 Play2Code 方法，让游戏智能体与不接触评分标准的 GUI 试玩智能体通过共享记忆迭代生成、试玩并改进游戏。在三个前沿基座模型上，Play2Code 取得 66.8% 的评分标准通过率，分别比单次生成和智能体编码基线高出 37.1 和 14.6 个百分点，且分数随迭代轮次单调提升。
正文
Authors:Yixu Huang, Bo Li, Na Li, Zhe Wang, Kaijie Chen, Haonan Ge, Qingyi Si, Yuanzhe Shen, Ruihan Yang, Guangjing Wang, Hongcheng Guo
Abstract:Generating a game is not the same as making one playable. Existing code-generation approaches often translate a prompt directly into an artifact, leaving interaction-level failures undetected. We argue that game generation requires a player and study two roles for graphical user interface (GUI) agents. First, we introduce \textbf{PlaytestArena}, an evaluation environment containing 200 browser-based game-generation tasks across eight genres, each paired with rubrics of expected in-play behaviors. An independent GUI judge loads and plays each build to adjudicate these rubrics. Second, we propose \textbf{Play2Code}, in which a game agent and a rubric-blind GUI playtester iteratively generate, play, and refine games through shared memory. The playtester provides gameplay traces and actionable feedback, while a separate GPT-5.5 judge assigns final benchmark scores. Across three frontier backbones, Play2Code achieves a 66.8\% rubric pass rate, outperforming single-pass and agentic-coding baselines by 37.1 and 14.6 points, respectively. Its scores also improve monotonically across refinement rounds. Further analysis shows that GUI-agent feedback is fully logged and traceable, while its priorities vary substantially across model backbones. These results establish GUI playtesting as an evaluation and refinement signal for interactive code generation. Our project website is available at this https URL
| Subjects: | Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Human-Computer Interaction (cs.HC) |
| Cite as: | arXiv:2605.28258 [cs.SE] |
| (or arXiv:2605.28258v2 [cs.SE] for this version) | |
| https://doi.org/10.48550/arXiv.2605.28258 arXiv-issued DOI via DataCite |
Submission history
From: Yixu Huang [view email]
[v1]
Wed, 27 May 2026 10:08:48 UTC (21,993 KB)
[v2]
Fri, 2 Oct 2026 05:26:34 UTC (21,987 KB)
来源：arXiv：cs.AI · arxiv.org