基于价值的大型语言模型代理模拟,用于对信任和人际亲密的相互评估
Yuki Sakamoto1, Takahisa Uchida2, Hiroshi Ishiguro2
1Graduate School of Engineering Science, The University of Osaka, Toyonaka, 5608531, Japan. sakamoto.yuki@irl.sys.es.osaka-u.ac.jp.
Scientific reports
|November 25, 2025
概括
用大型语言模型 (LLM) 构建的人造社会中的价值相似性增强了代理人之间的信任和亲密关系. 这项研究验证了社会科学的LLM模拟,探索价值驱动的关系动力学.
科学领域:
- 人工智能的人工智能
- 社会模拟社会模拟
- 计算社会科学 计算社会科学
背景情况:
- 大型语言模型 (LLM) 使用具有定义特征的代理人模拟复杂的社会现象.
- 价值相似性对于人类社会中的信任和关系至关重要,但在人工的LLM社会中尚未探索.
研究的目的:
- 调查价值相似性对LLM代理人之间建立关系的影响.
- 评估LLM代理模拟作为社会科学理论的测试平台.
主要方法:
- 进行了两项实验:一项关于LLM价值可控性的初步研究和一项关于代理相互作用的主要实验.
- 拥有控制价值观的LLM代理人进行对话,以评估相互信任和人际亲密.
- 用英语和日语进行实验,以检查语言依赖.
主要成果:
- 具有较高价值相似性的LLM代理人表现出明显更大的相互信任和人际亲密.
- 这项研究证实了人工智能中价值调整和关系质量之间的正相关性.
结论:
- LLM代理模拟是测试社会科学理论的有效平台.
- 阐明了影响关系建立的价值相似机制.
- 这些发现为新的社会科学理论和见解提供了基础.
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