Value-based large language model agent simulation for mutual evaluation of trust and interpersonal closeness.

ABSTRACT: Large language models (LLMs) have emerged as powerful tools for simulating complex social phenomena using human-like agents with specific traits. In human societies, value similarity is important for building trust and close relationships; however, it remains unexplored whether this principle holds true in artificial societies comprising LLM agents. Therefore, this study investigates the influence of value similarity on relationship-building among LLM agents through two experiments. First, in a preliminary experiment, we evaluated the controllability of values in LLMs to identify the most effective model and prompt design for controlling the values. Subsequently, in the main experiment, we generated pairs of LLM agents imbued with specific values and analyzed their mutual evaluations of tr

SUBMITTER: Sakamoto Y 

PROVIDER: S-EPMC12644628 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature