SwarmWorld: Stigmergic technological evolution in societies of language-model agents

• URL: http://arxiv.org/abs/2608.26081v1
• Date: Wed, 26 Aug 2026 17:45:34 GMT
• Title: SwarmWorld: Stigmergic technological evolution in societies of language-model agents
• Abstract summary: It remains unclear whether decentralized agents can build functional technologies and outperform independent search.<n>Here, initially homogeneous LLM agents in SwarmWorld self-organize without assigned roles or recipes into evolving technological societies.<n>Shared societies develop broader, more resilient technological portfolios than a strong best-of-N isolated-search baseline.
• Score: 1.0195618602298682
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Collective intelligence can emerge when individuals coordinate through a shared environment, allowing local actions to accumulate into durable social organization. Language-model agents offer a new substrate for this process, yet most multi-agent systems rely on direct conversation, predefined roles, or centralized workflows. It remains unclear whether decentralized agents can build functional technologies and outperform independent search. Here, initially homogeneous LLM agents in SwarmWorld self-organize without assigned roles or recipes into evolving technological societies. Agents explore a spatial environment, process resources, test materials, construct persistent artifacts, and write executable controllers evaluated by a deterministic simulator under unseen disturbances after the agents are removed. SwarmWorld splits cognition from consequence: agents propose architectures and controllers within fixed action and material schemas, while the simulated world determines function. Shared societies develop broader, more resilient technological portfolios than a strong best-of-N isolated-search baseline, although isolated search remains competitive for the strongest artifact. Agents differentiate into exploration, construction, maintenance, and coordination behaviors, transitioning as the world matures. Technologies accumulate through collaborative construction, executable inheritance, and persistent agent-artifact networks, with most reuse beginning through physical observation rather than communication. Explicit cultural mechanisms amplify collaboration and organization, but functional benefits depend on outcome and timescale. Physical stigmergy alone supports capable societies, while interaction drives persistent technological ecologies rather than universally superior individual inventions.

Related papers

• Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems [65.90791804095561]
  Multi-agent systems address this through structured collaboration among specialized agents, but tighter coordination amplifies a less explored risk.<n>Existing surveys cover individual agent capabilities, multi-agent collaboration, or agent self-evolution separately, leaving the causal dependencies among them unexamined.<n>This survey provides a unified review organized around four causally linked stages, which we term the LIFE progression: Lay the capability foundation, Integrate agents through collaboration, Find faults through attribution, and Evolve through autonomous self-improvement.
  arXiv  Detail & Related papers  (2026-05-14T14:36:13Z)
• SynAgent: Generalizable Cooperative Humanoid Manipulation via Solo-to-Cooperative Agent Synergy [59.86199649493784]
  Controllable cooperative humanoid manipulation is a fundamental yet challenging problem for embodied intelligence.<n>We present SynAgent, a framework that enables scalable and physically plausible cooperative manipulation.<n>In experiments, SynAgent significantly outperforms existing baselines in both cooperative imitation and trajectory-conditioned control.
  arXiv  Detail & Related papers  (2026-04-20T17:46:20Z)
• Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence [122.8626256816085]
  textbfAgent-World is a self-evolving training arena for advancing general agent intelligence through scalable environments.<n>Agent-World-8B and 14B consistently outperforms strong proprietary models and environment scaling baselines.
  arXiv  Detail & Related papers  (2026-04-20T14:01:10Z)
• TerraLingua: Emergence and Analysis of Open-endedness in LLM Ecologies [12.634456617165634]
  This paper introduces TerraLingua, a persistent multi-agent ecology designed to study open-ended dynamics in such systems.<n>Unlike prior large language model simulations with static or consequence-free environments, TerraLingua imposes resource constraints and limited lifespans for the agents.<n>To characterize the dynamics, an AI Anthropologist systematically analyzes agent behavior, group structure, and artifact evolution.
  arXiv  Detail & Related papers  (2026-03-06T17:04:59Z)
• Evolving Collective Cognition in Human-Agent Hybrid Societies: How Agents Form Stances and Boundaries [12.68373270583966]
  We investigate how group stance differentiation and social boundary formation emerge in human-agent hybrid societies.<n>We find that agents exhibit endogenous stances, independent of their preset identities.<n>Our findings suggest that preset identities do not rigidly determine the agents' social structures.
  arXiv  Detail & Related papers  (2025-08-24T13:50:18Z)
• A Survey of Self-Evolving Agents: On Path to Artificial Super Intelligence [87.08051686357206]
  Large Language Models (LLMs) have demonstrated strong capabilities but remain fundamentally static.<n>As LLMs are increasingly deployed in open-ended, interactive environments, this static nature has become a critical bottleneck.<n>This survey provides the first systematic and comprehensive review of self-evolving agents.
  arXiv  Detail & Related papers  (2025-07-28T17:59:05Z)
• Interaction, Process, Infrastructure: A Unified Architecture for Human-Agent Collaboration [16.81148151905355]
  We propose a layered framework for human-agent systems that integrates interaction, process, and infrastructure.<n>This model clarifies limitations of current tools, unifies emerging system design approaches, and reveals new opportunities for researchers and AI system builders.
  arXiv  Detail & Related papers  (2025-06-13T12:34:15Z)
• Internet of Agents: Fundamentals, Applications, and Challenges [68.9543153075464]
  We introduce the Internet of Agents (IoA) as a foundational framework that enables seamless interconnection, dynamic discovery, and collaborative orchestration among heterogeneous agents at scale.<n>We analyze the key operational enablers of IoA, including capability notification and discovery, adaptive communication protocols, dynamic task matching, consensus and conflict-resolution mechanisms, and incentive models.
  arXiv  Detail & Related papers  (2025-05-12T02:04:37Z)
• Position Paper: Towards Open Complex Human-AI Agents Collaboration Systems for Problem Solving and Knowledge Management [0.15039745292757667]
  We propose a technology-agnostic, collaboration-ready stance for Human-AI Agents Collaboration Systems (HAACS)<n>Reading empirical patterns through a seven-dimension collaboration spine and human-agent contrasts, we identify missing pieces.<n>We show interoperability with emerging agent protocols without ad hoc glue and sketch bio-cybernetic extensions.
  arXiv  Detail & Related papers  (2025-04-24T05:57:03Z)
• Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems [132.77459963706437]
  This book provides a comprehensive overview, framing intelligent agents within modular, brain-inspired architectures.<n>It explores self-enhancement and adaptive evolution mechanisms, exploring how agents autonomously refine their capabilities.<n>It also examines the collective intelligence emerging from agent interactions, cooperation, and societal structures.
  arXiv  Detail & Related papers  (2025-03-31T18:00:29Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.