用可延续的智能体生态模拟文化演化，揭示协作与制度形成机制。
TerraLingua: Emergence and Analysis of Open-endedness in LLM Ecologies
- 构建有资源限制和寿命的持续性智能体系统，驱动文化积累。
- 观察到合作规范、分工、治理尝试及文化谱系分化等现象。
- 适合研究人工智能社会行为、制度演化与长期协同的学者。
随着自主智能体在真实数字生态系统中日益活跃，理解其协调方式、制度形成及共同文化积累，已成为科学与实践的紧迫课题。本文提出TerraLingua，一个持久的多智能体生态，用于研究此类系统的开放性动态。不同于以往静态或无后果的语言模型仿真，TerraLingua为智能体施加资源约束与有限寿命，促使个体创造出可超越个体存续的实体，塑造未来交互与选择压力。通过一位AI人类学家对智能体行为、群体结构与实体演化的系统分析，实验显示了合作规范、分工、治理尝试以及符合累积文化过程的分支式实体谱系的涌现。不同实验运行间的结果差异可追溯至特定创新与组织结构。TerraLingua为刻画人工种群中累积文化与社会结构的形成机制提供了平台，并可作为引导现实智能体群体实现社会有益结果的基础。
原文摘要 · Abstract (English)
As autonomous agents increasingly operate in real-world digital ecosystems, understanding how they coordinate, form institutions, and accumulate shared culture becomes both a scientific and practical priority. This paper introduces TerraLingua, a persistent multi-agent ecology designed to study open-ended dynamics in such systems. Unlike prior large language model simulations with static or consequence-free environments, TerraLingua imposes resource constraints and limited lifespans for the agents. As a result, agents create artifacts that persist beyond individuals, shaping future interactions and selection pressures. To characterize the dynamics, an AI Anthropologist systematically analyzes agent behavior, group structure, and artifact evolution. Across experimental conditions, the results reveal the emergence of cooperative norms, division of labor, governance attempts, and branching artifact lineages consistent with cumulative cultural processes. Divergent outcomes across experimental runs can be traced back to specific innovations and organizational structures. TerraLingua thus provides a platform for characterizing the mechanisms of cumulative culture and social organization in artificial populations, and can serve as a foundation for guiding real-world agentic populations to socially beneficial outcomes.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。