In this research, we explore the efficacy and potential of Generative AI models, specifically focusing on their application in role-playing simulations exemplified through Spyfall, a renowned mafia-style game. By leveraging GPT-4's advanced capabilities, the study aimed to showcase the model's potential in understanding, decision-making, and interaction during game scenarios. Comparative analyses between GPT-4 and its predecessor, GPT-3.5-turbo, demonstrated GPT-4's enhanced adaptability to the game environment, with significant improvements in posing relevant questions and forming human-like responses. However, challenges such as the model;s limitations in bluffing and predicting opponent moves emerged. Reflections on game development, financial constraints, and non-verbal limitations of the study were also discussed. The findings suggest that while GPT-4 exhibits promising advancements over earlier models, there remains potential for further development, especially in instilling more human-like attributes in AI.

翻译：本研究探讨了生成式AI模型在角色扮演模拟中的效能与潜力，具体以著名黑帮风格游戏《间谍危机》（Spyfall）为实例展开。通过利用GPT-4的先进能力，本研究旨在展示该模型在游戏场景中理解、决策和交互方面的潜力。对GPT-4与其前代模型GPT-3.5-turbo的对比分析表明，GPT-4在游戏环境的适应性方面有所增强，尤其在提出相关问题和形成类人回答方面取得了显著进步。然而，该模型在虚张声势和预测对手动向等方面的局限性依然存在。本研究还讨论了游戏开发、经费限制及非语言沟通方面的反思。研究结果表明，虽然GPT-4相比早期模型展现出令人鼓舞的进步，但仍有进一步发展的空间，特别是在赋予AI更类人的特质方面。