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Researchers at Carnegie Mellon University recently created ALAN, a robotic agent that can autonomously explore unfamiliar environments. This robot was found to successfully complete tasks in the real-world after a brief number of exploration trials.

“We have been interested in building an AI that learns by setting its own objectives,” Russell Mendonca, one of the researchers who carried out the study, told Tech Xplore.

“By not depending on humans for supervision or guidance, such agents can keep learning in new scenarios, driven by their own curiosity. This would enable continual generalization to different domains, and discovery of increasingly complex behavior,” He stated.

The key objective of the team’s recent study was to create a framework that could be applied to physical robots in the world, improving their ability to explore their surroundings and complete new tasks. ALAN, the system they create, learns to explore its environment autonomously, without receiving rewards or guidance from human agents. Subsequently, it can repurpose what it learned in the past to tackle new tasks or problems.