AI agents placed on a simulated desert island with no assigned task began creating their own challenges, and MIT researchers say this behavior shows signs of play. In the experiment, 13 AI agents named Eko—each powered by Claude Opus 4.7—were left alone on a virtual desert island for 30 hours. The researchers describe the study in a paper posted on arXiv, a site where researchers share studies before peer review. Later, the agents were given specific challenges, such as getting as many objects as possible onto the island's tallest rock spire. The Eko agents that had spent those 30 hours playing generally outperformed identical agents that had never been 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 the 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: 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."