Huang, Yubo

Imitating from auxiliary imperfect demonstrations via Adversarial Density Weighted Regression

2024 · arXiv (Cornell University)

We propose a novel one-step supervised imitation learning (IL) framework called Adversarial Density Regression (ADR). This IL framework aims to correct the policy learned on unknown-quality to match the expert distribution by utilizing demonstrations, without …