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逆强化学习的新型变分下界

💡 原文中文，约300字，阅读约需1分钟。

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内容提要

VLB-IRL是一种新的逆向强化学习方法，通过最大化下界来学习奖励函数和寻找达到专家级性能的策略。该方法可以消除手动奖励设计的需要，优于现有算法。

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