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APReL: A Library for Active Preference-based Reward Learning Algorithms

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 نشر من قبل Erdem B{\\i}y{\\i}k
 تاريخ النشر 2021
  مجال البحث الهندسة المعلوماتية
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Reward learning is a fundamental problem in robotics to have robots that operate in alignment with what their human user wants. Many preference-based learning algorithms and active querying techniques have been proposed as a solution to this problem. In this paper, we present APReL, a library for active preference-based reward learning algorithms, which enable researchers and practitioners to experiment with the existing techniques and easily develop their own algorithms for various modules of the problem.

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