The emergence of social norms has attracted much interest in a wide array of
disciplines, ranging from social science and cognitive science to artificial
intelligence. In this paper, we propose the first generative agent architecture
that empowers the emergence of social norms within a population of large
language model-based agents. Our architecture, named CRSEC, consists of four
modules: Creation & Representation, Spreading, Evaluation, and Compliance. Our
architecture addresses several important aspects of the emergent processes all
in one: (i) where social norms come from, (ii) how they are formally
represented, (iii) how they spread through agents' communications and
observations, (iv) how they are examined with a sanity check and synthesized in
the long term, and (v) how they are incorporated into agents' planning and
actions. Our experiments deployed in the Smallville sandbox game environment
demonstrate the capability of our architecture to establish social norms and
reduce social conflicts within large language model-based multi-agent systems.
The positive outcomes of our human evaluation, conducted with 30 evaluators,
further affirm the effectiveness of our approach.

我们提出了一个名为 CRSEC 的建模代理架构，能够在大型基于语言模型的代理人群体中产生社会规范，通过 Creation＆Representation、Spreading、Evaluation 和 Compliance 四个模块处理社会规范的涌现过程，并将其纳入代理人的规划和行动中，实验证明了该架构在减少社会冲突方面的有效性。