Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling

• URL: http://arxiv.org/abs/2506.04699v1
• Date: Thu, 05 Jun 2025 07:21:13 GMT
• Title: Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling
• Authors: Bihan Xu, Shiwei Zhao, Runze Wu, Zhenya Huang, Jiawei Wang, Zhipeng Hu, Kai Wang, Haoyu Liu, Tangjie Lv, Le Li, Changjie Fan, Xin Tong, Jiangze Han,
• Abstract summary: We take a preliminary step in introducing a novel approach using Large Language Models (LLMs) in MMO economy simulation.<n>We design LLM-driven agents with human-like decision-making and adaptability.<n>These agents are equipped with the abilities of role-playing, perception, memory, and reasoning, addressing the aforementioned challenges effectively.
• Score: 53.26311872828166
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Within the domain of Massively Multiplayer Online (MMO) economy research, Agent-Based Modeling (ABM) has emerged as a robust tool for analyzing game economics, evolving from rule-based agents to decision-making agents enhanced by reinforcement learning. Nevertheless, existing works encounter significant challenges when attempting to emulate human-like economic activities among agents, particularly regarding agent reliability, sociability, and interpretability. In this study, we take a preliminary step in introducing a novel approach using Large Language Models (LLMs) in MMO economy simulation. Leveraging LLMs' role-playing proficiency, generative capacity, and reasoning aptitude, we design LLM-driven agents with human-like decision-making and adaptability. These agents are equipped with the abilities of role-playing, perception, memory, and reasoning, addressing the aforementioned challenges effectively. Simulation experiments focusing on in-game economic activities demonstrate that LLM-empowered agents can promote emergent phenomena like role specialization and price fluctuations in line with market rules.

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