143 citations · 213 across the 15 of their papers we have counts for
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cs.LG2020★ 1 cited
DERAIL: Diagnostic Environments for Reward And Imitation Learning
Pedro Freire, Adam Gleave, Sam Toyer +1
The objective of many real-world tasks is complex and difficult to procedurally specify. This makes it necessary to use reward or imitation learning algorithms to infer a reward or…
cs.LG2020★ 7 cited
The MAGICAL Benchmark for Robust Imitation
Sam Toyer, Rohin Shah, Andrew Critch +1
Imitation Learning (IL) algorithms are typically evaluated in the same environment that was used to create demonstrations. This rewards precise reproduction of demonstrations in on…