Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-free RL

Reward-free reinforcement learning (RF-RL), a recently introduced RL paradigm, relies on random action-taking to explore the unknown environment without any reward feedback information. While the primary goal of the exploration phase in RF-RL is to reduce the uncertainty in the estimated model with...

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Bibliographische Detailangaben

Hauptverfasser:	Huang, Ruiquan, Yang, Jing, Liang, Yingbin
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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