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Found 2 papers, 1 papers with code
Dropout Q-Functions for Doubly Efficient Reinforcement Learning
To make REDQ more computationally efficient, we propose a method of improving computational efficiency called DroQ, which is a variant of REDQ that uses a small ensemble of dropout Q-functions.
Utilizing Skipped Frames in Action Repeats via Pseudo-Actions
The key idea of our method is making the transition between action-decision points usable as training data by considering pseudo-actions.
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