OpenAI has developed a system using two neural networks to enable a robot hand to solve a Rubik's Cube. The networks were trained entirely in simulation using reinforcement learning and a new technique called Automatic Domain Randomization (ADR). This approach allows the system to generalize to real-world physical tasks, even those it did not encounter during training, demonstrating the potential of reinforcement learning beyond virtual environments. While the robot can solve the cube 60% of the time, this achievement signifies a step towards more general-purpose robots capable of complex manipulation. AI
RANK_REASON Demonstration of reinforcement learning in a physical task using simulation and a novel randomization technique.
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