30 citations · 31 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Local Nonparametric Meta-Learning
Wonjoon Goo, Scott Niekum
A central goal of meta-learning is to find a learning rule that enables fast adaptation across a set of tasks, by learning the appropriate inductive bias for that set. Most meta-le…
cs.LG2019
Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations
Daniel S. Brown, Wonjoon Goo, Scott Niekum
The performance of imitation learning is typically upper-bounded by the performance of the demonstrator. While recent empirical results demonstrate that ranked demonstrations allow…
cs.LG2019★ 30 cited
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan +1
A critical flaw of existing inverse reinforcement learning (IRL) methods is their inability to significantly outperform the demonstrator. This is because IRL typically seeks a rewa…