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RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Zhao, Yujie, Escamill, Jose Efraim Aguilar, Lu, Weyl, Wang, Huazheng
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

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