10 citations · 10 across the 2 of their papers we have counts for
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cs.LG2022★ 10 cited
In-context Reinforcement Learning with Algorithm Distillation
Michael Laskin, Luyu Wang, Junhyuk Oh +11
We propose Algorithm Distillation (AD), a method for distilling reinforcement learning (RL) algorithms into neural networks by modeling their training histories with a causal seque…
cs.LG2021
Wasserstein Distance Maximizing Intrinsic Control
Ishan Durugkar, Steven Hansen, Stephen Spencer +1
This paper deals with the problem of learning a skill-conditioned policy that acts meaningfully in the absence of a reward signal. Mutual information based objectives have shown so…