Generative AI in Mafia-like Game Simulation

• URL: http://arxiv.org/abs/2309.11672v1
• Date: Wed, 20 Sep 2023 22:38:34 GMT
• Title: Generative AI in Mafia-like Game Simulation
• Authors: Munyeong Kim and Sungsu Kim
• Abstract summary: The study aimed to showcase the model's potential in understanding, decision-making, and interaction during game scenarios. The findings suggest that while GPT-4 exhibits promising advancements over earlier models, there remains potential for further development.
• Score: 2.44755919161855
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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