Using a novel capability to reason about shape, function, and attachment of unrelated parts, researchers have for the first time successfully trained an intelligent agent to create basic tools by combining objects.

The breakthrough comes from Georgia Tech’s Robot Autonomy and Interactive Learning (RAIL) research lab and is a significant step toward enabling intelligent agents to devise more advanced tools that could prove useful in hazardous—and potentially life-threatening—environments.

The concept may sound familiar. It’s called “MacGyvering,” based off the name of a 1980s—and recently rebooted—television series. In the series, the title character is known for his unconventional problem-solving ability using differing resources available to him.

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