2 papers
cs.RO2023
Diagnosing and Augmenting Feature Representations in Correctional Inverse Reinforcement Learning
Inês Lourenço, Andreea Bobu, Cristian R. Rojas +1
Robots have been increasingly better at doing tasks for humans by learning from their feedback, but still often suffer from model misalignment due to missing or incorrectly learned…
cs.LG2023
Optimal Transport for Correctional Learning
Rebecka Winqvist, Inês Lourenco, Francesco Quinzan +2
The contribution of this paper is a generalized formulation of correctional learning using optimal transport, which is about how to optimally transport one mass distribution to ano…