标题： 生成式人工智能在开源游戏开发中的实证研究：工具、任务和开发者挑战 显示英文标题

标题： An Empirical Study of GenAI Adoption in Open-Source Game Development: Tools, Tasks, and Developer Challenges

摘要： 生成式人工智能（GenAI）能力的不断提升已经开始重塑游戏的设计和开发方式，为内容创作、游戏玩法模拟和设计构思提供了新的工具。 尽管之前的研究已经探讨了人工智能在游戏中的传统用途，例如控制代理或生成程序内容。 但对于GenAI在现实世界情境中被开发者采用的实证理解仍然有限，尤其是在开源社区中。 本研究旨在通过分析GitHub上的问题讨论，探索GenAI技术如何被讨论、采用并整合到开源游戏开发中。 我们通过将与GenAI相关的问题与涉及传统人工智能（TradAI）和NonAI主题的问题进行比较，研究与GenAI相关的工具、任务和挑战。 我们的目标是揭示GenAI在使用模式、开发者关注点和集成实践方面与其他方法的不同之处。 为了实现这一目标，我们构建了一个包含讨论人工智能相关话题的开源游戏仓库的数据集。 我们对GitHub问题的分层样本应用了开放卡片排序和主题分析，并按类型和内容进行标记。 这些注释使得可以在GenAI、TradAI和NonAI组之间进行比较分析，并提供关于GenAI如何塑造开源游戏开发人员的工作流程和痛点的见解。 显示英文摘要

摘要： The growing capabilities of generative AI (GenAI) have begun to reshape how games are designed and developed, offering new tools for content creation, gameplay simulation, and design ideation. While prior research has explored traditional uses of AI in games, such as controlling agents or generating procedural content. There is limited empirical understanding of how GenAI is adopted by developers in real-world contexts, especially within the open-source community. This study aims to explore how GenAI technologies are discussed, adopted, and integrated into open-source game development by analyzing issue discussions on GitHub. We investigate the tools, tasks, and challenges associated with GenAI by comparing GenAI-related issues to those involving traditional AI (TradAI) and NonAI topics. Our goal is to uncover how GenAI differs from other approaches in terms of usage patterns, developer concerns, and integration practices. To address this objective, we construct a dataset of open-source game repositories that discuss AI-related topics. We apply open card sorting and thematic analysis to a stratified sample of GitHub issues, labelling each by type and content. These annotations enable comparative analysis across GenAI, TradAI, and NonAI groups, and provide insight into how GenAI is shaping the workflows and pain points of open-source game developers.