105 citations · 179 across the 5 of their papers we have counts for
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cs.LG2020
Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER
Markus Holzleitner, Lukas Gruber, José Arjona-Medina +2
We prove under commonly used assumptions the convergence of actor-critic reinforcement learning algorithms, which simultaneously learn a policy function, the actor, and a value fun…
cs.LG2020
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution
Vihang P. Patil, Markus Hofmarcher, Marius-Constantin Dinu +5
Reinforcement learning algorithms require many samples when solving complex hierarchical tasks with sparse and delayed rewards. For such complex tasks, the recently proposed RUDDER…