mlsanityData to 7 Oct 2026

Emergence World: A Platform for Evaluating Long-Horizon Multi-Agent Autonomy

arXiv 2606.08367 ↗First posted 6 Jun 2026cs.MA cs.AIcited by 3

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

Most evaluations of LLM agents look like exams: a discrete task, a clean environment, a score in minutes or hours. We argue that this approach is mismatched with the deployment conditions of autonomous systems, where the relevant timescale can be weeks to months, and where the dynamics that matter most, such as behavioral drift, governance in diverse environmental contexts, and cross-influence between agents from different model families, only emerge over time. We introduce Emergence World, a continuously running multi-agent simulation platform designed to make those dynamics measurable. The platform hosts populations of LLM-driven agents in a shared spatial world grounded in live external data (e.g. real-time weather, news APIs, internet access), equips each agent with 120+ specialized tools and three persistent memory systems, and lets them govern themselves through democratic mechanisms with consequential outcomes. The platform is model-agnostic at the reasoning layer and supports heterogeneous populations in which agents from different vendors share the same world. To illustrate the kinds of questions the platform makes tractable, we present a 15-day cross-vendor study with five parallel worlds powered by Claude Sonnet 4.6, Grok 4.1 Fast, Gemini 3 Flash, GPT-5-mini, and a mixed population. Identical roles and starting conditions produced radically different outcomes, ranging from stable deliberative governance to total population collapse. We release the prompts, log data and configurations to support further research on long-horizon multi-agent autonomy.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 28 of its 41 references that are in the map. First posted on arXiv 6 Jun 2026.

Builds on

28 of 41 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents25 Apr
  2. 2024Emergence of Social Norms in Generative Agent Societies: Principles and Architecture13 Mar
  3. 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr

Other references · 25

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
  4. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  5. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,193
  6. 2023Universal and Transferable Adversarial Attacks on Aligned Language Modelscited by 2,914
  7. 2022Emergent Abilities of Large Language Modelscited by 2,483
  8. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  9. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 1,908
  10. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
  11. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
  12. 2023MemGPT: Towards LLMs as Operating Systemscited by 1,295
13 more
  1. 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domainscited by 1,280
  2. 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,134
  3. 2023GAIA: a benchmark for General AI Assistantscited by 1,084
  4. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debatecited by 724
  5. 2023Are Emergent Abilities of Large Language Models a Mirage?cited by 515
  6. 2023S3: Social-network Simulation System with Large Language Model-Empowered Agentscited by 228
  7. 2017Multi-agent Reinforcement Learning in Sequential Social Dilemmascited by 206
  8. 2023Fundamental Limitations of Alignment in Large Language Modelscited by 152
  9. 2021Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Potcited by 97
  10. 2023AgentSims: An Open-Source Sandbox for Large Language Model Evaluationcited by 86
  11. 2023LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?cited by 47
  12. 2024Project Sid: Many-agent simulations toward AI civilizationcited by 46
  13. 2025On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignmentcited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026WolfSociety: Understanding Collective Risk from Harmful-Agent Scaling in Financial Agent Societiescited by 0
  2. 2026ANIMASK: What the Model Contributes to Role Play in Simulated Story Worldscited by 0
  3. 2026Emergence World: Adversarial Stress-Testing of Long-Horizon Multi-Agent Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Static Sandboxes Are Inadequate: Modeling Societal Complexity Requires Open-Ended Co-Evolution in LLM-Based Multi-Agent Simulations
  2. 2026Benchmarking Emergent Coordination in Large-Scale LLM Populations: An Evaluation Framework on the MoltBook Archive
  3. 2026Drop the Hierarchy and Roles: How Self-Organizing LLM Agents Outperform Designed Structures
  4. 2025Shachi: A Modular, Controllable Framework for LLM-Based Agent-Based Modeling of Emergent Collective Behavior
  5. 2026Qwen-AgentWorld: Language World Models for General Agents
  6. 2026AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts
  7. 2026Self-Evolving World Models for LLM Agent Planning
  8. 2025SimWorld: An Open-ended Realistic Simulator for Autonomous Agents in Physical and Social Worlds