Large Language Model Assisted Experiment Design with Generative Human-Behavior Agents
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.
Authors
- Zeyu Zheng (ORCID: https://orcid.org/0000-0001-5653-152X)
- Haoyu Liu (ORCID: https://orcid.org/0000-0002-8998-1217)
- Tingyu Zhu (ORCID: https://orcid.org/0009-0003-0946-4194)
- Zizhao Zhang (ORCID: https://orcid.org/0000-0001-7329-6461)
- Yifu Tang (ORCID: https://orcid.org/0000-0003-1146-5746)
Institutions
- University of California, Berkeley (US)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/wsc63780.2024.10838726
- Citations
- 1
- Primary Topic
- Machine Learning and Data Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.35