19 citations · 19 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 19 cited
Dropout Q-Functions for Doubly Efficient Reinforcement Learning
Takuya Hiraoka, Takahisa Imagawa, Taisei Hashimoto +2
Randomized ensembled double Q-learning (REDQ) (Chen et al., 2021b) has recently achieved state-of-the-art sample efficiency on continuous-action reinforcement learning benchmarks.…
cs.LG2021
Utilizing Skipped Frames in Action Repeats via Pseudo-Actions
Taisei Hashimoto, Yoshimasa Tsuruoka
In many deep reinforcement learning settings, when an agent takes an action, it repeats the same action a predefined number of times without observing the states until the next act…