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.

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

Zeyu Zheng, Haoyu Liu, Tingyu Zhu, Zizhao Zhang et al.
1 citations
Machine Learning and Data Classification
0.35
article

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

Zeyu Zheng, Haoyu Liu, Tingyu Zhu, Zizhao Zhang, Yifu Tang
article en
1 citations

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.

University of California, Berkeley (US)
Openalex Percentile: Top 30%
Machine Learning and Data Classification
0.35
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