Few things reveal the limits of someone’s problem-solving skills faster than a Rubik’s Cube, the multicolored, three-dimensional puzzle that has befuddled so many since the 1970s.
This week, the University of California at Irvine announced that an artificial intelligence system solved the puzzle in just over a second, besting the current human world record by more than two seconds.
The system, known as DeepCubeA — a reinforcement-learning algorithm programmed by UCI computer scientists and mathematicians — solved the puzzle without prior knowledge of the game or coaching from its human handlers, according to the university.
The feat is even more impressive considering that there are billions of potential moves available to a Rubik’s Cube player, with the puzzle’s six sides and nine sections, but only one goal: each of the cube’s six sides displaying a solid color.
“Artificial intelligence can defeat the world’s best human chess and Go players, but some of the more difficult puzzles, such as the Rubik’s Cube, had not been solved by computers, so we thought they were open for AI approaches,” senior author Pierre Baldi, a professor of computer science, said in a statement released by the university. “The solution to the Rubik’s Cube involves more symbolic, mathematical and abstract thinking, so a deep learning machine that can crack such a puzzle is getting closer to becoming a system that can think, reason, plan and make decisions.”
They asked artificial intelligence to create a game. One of its first ideas involved exploding Frisbees.
Researchers published their findings in Nature Machine Intelligence, noting that their system’s algorithm was given 10 billion combinations of the puzzle. The goal, researchers wrote, was to solve each combination within 30 moves.
DeepCubeA solved 100 percent of test configurations, researchers wrote, and located the shortest path to solving the puzzle more than 60 percent of the time. Researchers said the algorithm also works on similar games, such as the sliding-tile puzzles Lights Out and Sokoban.
Highly skilled humans are able to tackle a Rubik’s Cube in about 50 moves, but the AI system is able to solve the cube in about 20 moves, usually in the minimum number of steps possible, the researchers said.
The UCI algorithm relies on a neural network — a set of algorithms designed to find underlying relationships by mimicking how the human brain processes information. The algorithm also relied on machine learning techniques, a system that allows AI to learn by identifying patterns and using inference with minimal human intervention.
But since the algorithm was programmed merely to solve the puzzle, researchers were left with a limited understanding of how it did so. To perfect its abilities, DeepCube trained in isolation for two days, refining its skill as it unpacked the Rubik’s Cube.
“It learned on its own,” Baldi told the BBC. “My best guess is that the AI’s form of reasoning is completely different from a human’s.”
Human world records for solving the Rubik’s Cube are down to about 3.5 seconds, more than 15 seconds less than record times in the early 1980s, according to the World Cube Association.
The UCI algorithm is impressive, but it’s not the fastest nonhuman conqueror of the Rubik’s Cube. In Germany, researchers built a robot in 2016 named Sub1 Reloaded that solved the puzzle in 0.637 seconds.
Last year, that record was broken by a pair of American researchers who built a robot that solved the puzzle in 0.38 seconds.
A hit-and-run scooter crash nearly killed him. Now he’s fighting for the data that could reveal the rider’s identity.
Google’s balloon project has a new test: Providing Internet access to ‘mountainous villagers’ in Kenya
Wearable technology started by tracking steps. Soon, it may allow your boss to track your performance.