TerraLingua: Emergence and Analysis of Open-endedness in LLM Ecologies

Fuente: arXiv
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Main Authors: Paolo, Giuseppe, Warner, Jamieson, Shahrzad, Hormoz, Hodjat, Babak, Miikkulainen, Risto, Meyerson, Elliot
Format: Preprint
Published: 2026
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author Paolo, Giuseppe
Warner, Jamieson
Shahrzad, Hormoz
Hodjat, Babak
Miikkulainen, Risto
Meyerson, Elliot
author_facet Paolo, Giuseppe
Warner, Jamieson
Shahrzad, Hormoz
Hodjat, Babak
Miikkulainen, Risto
Meyerson, Elliot
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2603_16910
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle TerraLingua: Emergence and Analysis of Open-endedness in LLM Ecologies
Paolo, Giuseppe
Warner, Jamieson
Shahrzad, Hormoz
Hodjat, Babak
Miikkulainen, Risto
Meyerson, Elliot
Multiagent Systems
Artificial Intelligence
Physics and Society
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.
title TerraLingua: Emergence and Analysis of Open-endedness in LLM Ecologies
topic Multiagent Systems
Artificial Intelligence
Physics and Society
url https://arxiv.org/abs/2603.16910