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Through RL (reinforcement learning, or reward-driven optimization), o1 learns to hone its chain of thought and refine the strategies it uses — ultimately learning to recognize and correct its ...

We review encoding and hardware-independent formulations of optimization problems for quantum computing. Using this generalized approach, an extensive library of optimization problems from the ...