  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.

Artificial Intelligence;Human-Computer Interaction