CompeteAI: An Artificial Intelligence AI Framework that Understands the Competition Dynamics of Large Language Model-based Agents

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The CompeteAI framework is designed to study competition dynamics using Large Language Model (LLM) based agents in a simulated small-town environment. This framework allows the examination of competitive behaviors among restaurant agents managed through GPT-4, capturing both micro and macro-level competitive dynamics. Key findings reveal sophisticated agent behaviors, such as strategy differentiation, customer satisfaction, and the Matthew Effect, demonstrating that competition improves product quality over time. The research shows that LLM-based agents can simulate realistic competitive environments, providing insights into market behaviors and customer decision-making.