NeurIPS 2020

Curriculum learning for multilevel budgeted combinatorial problems

Meta Review

The paper proposes a deep reinforcement learning approach for multi-level combinatorial optimization. Reviewers agree on accepting the paper and recognize its novelty and writing standard. The paper merits publication due to its novelty (combining combinatorial optimization with RL), being well-written and promising experimental results. The rebuttal addressed successfully concerns raised by reviewers. The experimental part of the paper did not convince the reviewers, though, due to small problem sizes. The recommendation for the paper is accept.