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cs.LG2024
Adaptive -Network: On-the-fly Target Selection for Deep Reinforcement Learning
Théo Vincent, Fabian Wahren, Jan Peters +2
Deep Reinforcement Learning (RL) is well known for being highly sensitive to hyperparameters, requiring practitioners substantial efforts to optimize them for the problem at hand.…
cs.LG2024
Iterated -Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning
Théo Vincent, Daniel Palenicek, Boris Belousov +2
The vast majority of Reinforcement Learning methods is largely impacted by the computation effort and data requirements needed to obtain effective estimates of action-value functio…