According to foreign media CNET, it is relatively simple to create an algorithm that can solve the Rubik's Cube. However, unlocking the Rubik's Cube without human assistance may be a completely different task. Stephen McAleer of the University of California and his colleagues believe they have solved this problem and have adopted a process called "self-learning incremental iteration".
McAleer and his team called this process "a new type of reinforcement learning algorithm that can teach the algorithm how to solve the Rubik's Cube without human assistance." They claim that this learning algorithm can solve 100% in 30 steps Randomly disrupts the Rubik's Cube-this is comparable to or better than human performance.
This type of algorithm differs from algorithms that surpass human performance in board games. These systems are "reinforcement learning" systems. The system will check if each proposed step is an improvement after completing the puzzle.
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