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問題 1 / 65

Which of the following is most appropriate as the key difference between supervised learning and reinforcement learning?

Supervised learning is the same as reinforcement learning in that it deals only with problems of maximizing rewards.
Reinforcement learning is the same as supervised learning in that it requires large amounts of labeled data.
Supervised learning does not interact with the environment, but reinforcement learning does not always interact with the environment.
They are the same in that both always use the correct label as the supervisory signal.
Supervised learning learns from pairs of inputs and correct outputs, whereas reinforcement learning differs in that it learns a policy through trials of actions and rewards.

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