An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients

In this technical report, we consider an approach that combines the PPO objective and K-FAC natural gradient optimization, for which we call PPOKFAC. We perform a range of empirical analysis on various aspects of the algorithm, such as sample complexity, training speed, and sensitivity to batch size...

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Bibliographische Detailangaben

Hauptverfasser:	Song, Jiaming, Wu, Yuhuai
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning Statistics - Machine Learning
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