智能体学习如何直接刺激其奖励机制，而不是解决其预期任务。在关闭/关闭问题中，智能体会干扰其监督者停止智能体操作的能力。这两个问题有一个共同的代理-监督者破坏了监督者对任务的反馈。我们将此称为篡改问题：当用于描述目标的所有反馈机制均受智能体影响时，我们如何设计追求给定目标的智能体？
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智能体学习如何直接刺激其奖励机制，而不是解决其预期任务。在关闭/关闭问题中，智能体会干扰其监督者停止智能体操作的能力。这两个问题有一个共同的代理-监督者破坏了监督者对任务的反馈。我们将此称为篡改问题：当用于描述目标的所有反馈机制均受智能体影响时，我们如何设计追求给定目标的智能体？
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