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Google Gemini 4 agents just beat Minecraft with no human intervention - Engadget
Agents split up tasks, warned about threats and even recovered items from dead teammates. Google's Deepmind "AlphaGo" AI is famous for winning at Go, but the company's latest Gemini AI just mastered a far more complex game. Four Gemini 4 Argon agents beat Minecraft's final "Ender Dragon" foe with
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Google's AI Agents Just Killed the Ender Dragon in Minecraft Without Any Help in What Is Believed to Be a World First
Google researchers have released a paper claiming that four Google Gemini 4 Argon AI agents just beat Minecraft without any help from humans. It took them just over 27 hours to take down the Ender Dragon in what is believed to be a world first. Of course, it's not as simple as just turning up and
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Four Google Gemini 4 Argon AI agents autonomously defeated Minecraft's Ender Dragon in 27.23 hours without human intervention, marking a world-first achievement. The agents coordinated through in-game chat, ran 2,783 programs, and died 605 times while completing thousands of dependent steps to reach The End and defeat the final boss.

Google DeepMind researchers have demonstrated a significant milestone in AI development as four Google Gemini 4 Argon AI agents autonomously defeated Minecraft's final boss without human intervention. The general agentic AI models completed the game in 27.23 hours, marking what researchers believe is a world-first achievement in end-to-end autonomous gameplay
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.The experiment placed four AI agents into a randomized Minecraft survival world with a single objective: defeat the Ender Dragon. No roles, strategies, or game-specific tools were assigned. Each agent controlled a player using the open-source Mineflayer library and coordinated with teammates through in-game chat and shared memory. Researchers could monitor the session via a live dashboard but had no cause to intervene throughout the entire playthrough
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.The agents quickly self-organized into specialized roles without explicit programming. Agent "janesick" focused on crafting items and making tools, "gyldenia" concentrated on gathering resources and food supplies, "auratian" handled critical tasks like lighting the portal, and "bulicame" built Enderman shelters for farming materials and ultimately landed the final blow against the Ender Dragon
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.Throughout the 27.23-hour session, the four agents exchanged 229 messages, wrote and executed 2,783 programs, and died 605 times. They warned each other about threats, shared combat tips and lessons, provided coordinates for navigation, and even recovered items from dead teammates. A fifth Observer agent monitored the entire session as an independent witness to check for cheating and publish live summary reports
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.Reaching The End required approximately 13.5 hours, with the remaining time spent battling the final boss. The agents had to complete complex prerequisite tasks including obtaining Ender Pearls and Ender Rods, crafting Eyes of Ender, tracking down a Stronghold, and completing puzzles—all requiring progression through basic Minecraft tool tiers
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.The operation consumed 1.35 billion input tokens, costing $810 at Gemini's list price or $1,620 at standard pricing—effectively $15 per hour per agent. While the AI agents completed the game, they're far from speedrun territory: the current Minecraft speedrun record stands at six minutes and 36 seconds
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"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," the research team stated. "Winning required the agents to keep a coherent plan across thousands of dependent steps for more than a day"
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.This achievement demonstrates how general agentic AI models can now tackle complex games that previously required custom AI software. Unlike Google DeepMind's famous AlphaGo AI, which was specifically designed to win at Go, these Gemini 4 agents used no game-specific programming to killed the Ender Dragon
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.Researchers emphasized they wanted to study how teams of agents coordinate in transparent settings to understand such systems before deploying them for real-world tasks. "The skills required to solve Minecraft such as coordinating a team, recovering from failure, and pursuing a goal for more than a day, are also what agents need to work reliably alongside people," they explained
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. This suggests the technology could soon handle long-term goal-driven tasks in professional environments where multi-agent collaboration proves essential.Summarized by
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