Large Language Model Assisted Experiment Design with Generative Human-Behavior Agents

Haoyu Liu, Yifu Tang, Zizhao Zhang, Zeyu Zheng, Tingyu Zhu

Abstract: Experiment design, despite its wide use in the fields such as economics, sociology and business operations, can sometimes encounter challenges or ethical issues when getting real human beings involved. On the other hand, the development of large language models (LLM) such as ChatGPT has empowered the development of generative agents with believable human behavior. This work develops an implementation framework to use LLM-empowered generative agents to assist experiment design where it is prohibitive to involve real human beings.