NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:2298
Title:Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints

The paper proposes a really interesting and novel variant of inverse RL with a nice formalization. The proposed algorithms are suitable. While the reviewers felt that the empirical results were weak (lack of scalability and linear reward function limitation), they thought that this was outweighed by the novelty of the problem and the significance of the contribution.