{"slug": "a-team-of-gemini-4-argon-agents-beats-minecraft", "title": "A team of Gemini 4 Argon agents beats Minecraft", "summary": "A team of four Gemini 4 Argon agents achieved what the researchers describe as the first end-to-end autonomous completion of Minecraft, defeating the Ender Dragon in 27 hours and 14 minutes on Easy difficulty from a randomly generated world, according to an arXiv paper submitted 15 Oct 2026. Each agent controlled a player through the open-source Mineflayer library and coordinated via in-game chat and shared memory, writing 2,783 programs and dying 605 times with no human-assigned roles or game logic. The authors argue the run demonstrates long-horizon planning and multi-agent coordination across thousands of dependent steps, capabilities they say real-world software engineering and enterprise tasks demand.", "body_md": "# Computer Science > Artificial Intelligence\n\n  [Submitted on 15 Oct 2026]\n\n# Title:A team of Gemini 4 Argon agents beats Minecraft\n\n[View PDF](https://arxiv.org/pdf/2610.22319)\n\n[HTML (experimental)](https://arxiv.org/html/2610.22319v1)\n\nAbstract:We placed four Gemini 4 Argon agents in a sandboxed Minecraft survival world and gave them one goal: defeat the Ender Dragon. Each agent controlled a player via an open-source library called Mineflayer and coordinated with its teammates through in-game chat and shared memory. No one assigned roles or wrote game logic. The agents planned, wrote, and debugged every program themselves. Researchers could watch the run on a live dashboard and pause or stop it at any time, but they had no cause to intervene. Starting from a randomly generated world on Easy difficulty, the team wrote 2,783 programs and defeated the dragon in 27 hours and 14 minutes, dying 605 times along the way. To our knowledge, this is the first end-to-end autonomous completion of Minecraft by AI agents, achieved using only the standard Mineflayer library without pre-scouted seeds or other game-specific tools written by humans. Winning required the agents to keep a coherent plan across thousands of dependent steps for more than a day. Complex real-world software engineering and enterprise tasks demand the same long-horizon coding and multi-agent coordination. We describe the setup, how the run unfolded, the team's strategies (dividing the work, sharing what they learned, recovering each other's items), and the limits of the result.\n    \n\n### Additional Features\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer \n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers \n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps \n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations \n\n*(*[What are Smart Citations?](https://www.scite.ai/))\n# Code, Data and Media Associated with this Article\n\nalphaXiv \n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers \n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub \n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub \n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face \n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast \n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))\n# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower \n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender \n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))\n# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [**Learn more about arXivLabs**](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/a-team-of-gemini-4-argon-agents-beats-minecraft", "canonical_source": "https://arxiv.org/abs/2610.22319", "published_at": "2026-10-21 06:36:59+00:00", "updated_at": "2026-10-21 07:11:20.004270+00:00", "lang": "en", "topics": ["ai-agents", "artificial-intelligence", "ai-research", "large-language-models"], "entities": ["Gemini 4 Argon", "Mineflayer", "Minecraft", "Ender Dragon", "arXiv"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/a-team-of-gemini-4-argon-agents-beats-minecraft", "markdown": "https://wpnews.pro/news/a-team-of-gemini-4-argon-agents-beats-minecraft.md", "text": "https://wpnews.pro/news/a-team-of-gemini-4-argon-agents-beats-minecraft.txt", "jsonld": "https://wpnews.pro/news/a-team-of-gemini-4-argon-agents-beats-minecraft.jsonld"}}