42 citations · 137 across the 13 of their papers we have counts for
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cs.LG2018★ 42 cited
Unsupervised Control Through Non-Parametric Discriminative Rewards
David Warde-Farley, Tom Van de Wiele, Tejas Kulkarni +3
Learning to control an environment without hand-crafted rewards or expert data remains challenging and is at the frontier of reinforcement learning research. We present an unsuperv…
cs.LG2018★ 16 cited
Fast deep reinforcement learning using online adjustments from the past
Steven Hansen, Pablo Sprechmann, Alexander Pritzel +2
We propose Ephemeral Value Adjusments (EVA): a means of allowing deep reinforcement learning agents to rapidly adapt to experience in their replay buffer. EVA shifts the value pred…