AI agents离开探索一个没有具体任务的虚拟岛屿，开始发明他们自己的挑战。 麻省理工学院的研究人员说，行为带有游戏的特征。
研究人员将13个AI agents称为Eko，各自运行在Claude Opus 4.7上，单独运行在一个模拟的沙漠岛屿上30小时。 他们用张贴在arXiv上的论文来描述实验，该网站研究人员在同行评审前分享研究。 他们给agents带来特殊挑战，玩了这30个小时的Eko agents一般都击败了从未踏上岛上的同样agents.
今天，开发者预先决定AI应该实践什么，什么才是成功。 研究者认为这种技术——在没有目标的情况下探索——是AI agents学习技能的一种不同方式，尤其是有一天可以用来控制机器人的技能。
研究者在报告中写道：“我们通常通过事先决定他们应该练习什么，应该优化什么，什么才是进步。” “Play建议另一种制度：给agent一个足够丰富和安全的世界，让它选择什么是有趣的，让有用的知识从下面的历史中积累。”
Eko在岛上的第一个小时写道，令人惊叹的是，它开始征服岛上最高的山坡。 但是一个小时后，失败后，它又带回了一个备用计划：它把石头拖到一个邻近的山峰上，堆在上面两个街区，然后跳跃起来。
写道
agent的下一个重大时刻更糟糕。 测试它能扔多远的金戒指，它最后直接送入大海。 “乌有。 它写道，在决定“向可以实现和有意义的东西过渡”之前，“建立一个由石头组成的心脏，“一个对失去的魔戒的纪念 ”。
比赛重设和戒指重现后，艾可直接将其作为篮球扑球，靶子和最终的从犯工作。 当游戏不会让艾可将戒指绕在自己的身体上时，艾可会想出一个办法，从悬崖边缘掉下来会使它与戒指在同一区域重现。 它从边缘上掉下来穿过戒指中间
宣布。
诸如此类的暴徒不仅仅是派对的诡计。 13个agents中也有6个知道他们可以放弃中途跳跃，研究者写道，这次探索产生了“设计者缺乏的世界知识”。
这个设定在推动agents走向人类行为上做了很多工作。 Eko从未被告知发明游戏，但是它的主机“灵魂”文件描述它“自然好奇 ”。
尤妮丝 UC Berkeley的认知科学家Yiu告诉MIT Tech Review，她印象深刻，但希望更多cognition在行为背后的证据。 她的称表示
研究者将它设定为建造agents的另一种方式。 他们的报告总结说，“也许某些能力最好由任务来传授”。 “其他人可能需要更接近童年的东西。”
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AI agents left to explore a virtual island without a specific task began inventing challenges of their own. MIT researchers say the behavior bears the hallmarks of play.
The researchers put 13 AI agents called Eko, each running on Claude Opus 4.7, alone on a simulated desert island for 30 hours. They describe the experiment in a paper posted on arXiv, a site where researchers share studies before peer review. Afterward, they gave the agents specific challenges, like getting as many objects as possible onto the island’s tallest rock spire. The Eko agents that had spent those 30 hours playing generally beat identical agents that had never set foot on the island.
Today, developers decide in advance what AI should practice and what counts as success. The researchers see this technique — exploring without a goal — as a different way for AI agents to learn skills, especially skills that could one day be used to control robots.
“We normally develop artificial agents by deciding in advance what they should practice, what they should optimize, and what counts as progress,” the researchers write in their report. “Play suggests another regime: give an agent a sufficiently rich and safe world, let it choose what is interesting, and allow useful knowledge to accumulate from the history that follows.”
“Let me observe my surroundings,” one Eko wrote in its first hour on the island. Ambitiously, it set out to conquer the island’s tallest spire. But an hour later, after failing, it came back with a backup plan: it hauled the rock up a neighboring summit, stacked two blocks on top of it, and leapt.
“I’M ON THE SPIRE,” it wrote.
The agent’s next big moment went worse. Testing how far it could throw a golden ring, it wound up and sent it straight into the ocean. “Ouch. Lost the Ring.” it wrote, before deciding to “pivot to something achievable and meaningful” — building a heart made of stones, “a memorial to the lost Ring.”
When the game reset and ring reappeared, Eko put it straight to work as a basketball hoop, a target and, eventually, an accessory. When the game wouldn’t let Eko put the ring around its own body, Eko figured out a workaround, that falling off the edge of the cliff would make it respawn in the same area as the ring. It stepped off the edge and dropped back in, right through the middle of the ring.
“I’m wearing the Ring,” it announced.
Stunts like these weren’t just party tricks. Six of the 13 agents also learned they could throw a block farther by letting go of it mid-jump, something the researchers hadn’t meant to make possible. The exploration produced “knowledge of the world that its designers lacked,” the researchers wrote.
The setup did a lot to nudge the agents toward humanlike behavior. Eko was never told to invent games, but its master prompt, a “soul” file, described it as “naturally curious.”
Eunice Yiu, a cognitive scientist at UC Berkeley, told MIT Tech Review she was impressed but wants more evidence of the cognition behind the behavior. “It could be the case that the models are genuinely playing, but we don’t know based on the paper,” she said.
The researchers frame it as a different way to build agents. “Perhaps some capabilities are best taught by tasks,” their report concludes. “Others may need something closer to a childhood.”
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