Action Branching Architectures for Deep Reinforcement Learning

AAAI 32: 4131-4138 (2018) Discrete-action algorithms have been central to numerous recent successes of deep reinforcement learning. However, applying these algorithms to high-dimensional action tasks requires tackling the combinatorial increase of the number of possible actions with the number of ac...

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Hauptverfasser:	Tavakoli, Arash, Pardo, Fabio, Kormushev, Petar
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning
Online-Zugang:	Volltext bestellen
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