MIT's Eko Agents Performed Better After Exploring a Simulated Island
Photo: TokenPost
MIT researchers let 13 AI agents called Eko explore a simulated island for 30 hours without assigning them a task. Each agent ran Claude Opus 4.7. In a later challenge to place objects on the island’s tallest rock spire, the agents that had explored generally did better than identical agents that had not. Open-ended exploration could help agents acquire useful skills, including skills that may eventually apply to robots. The approach differs from training that sets an agent’s task and measure of success in advance. Eko’s instructions described it as “naturally curious,” but did not tell it to invent games.
Source: TokenPost
