Reviews: Learning to Perform Local Rewriting for Combinatorial Optimization

After rebuttal: The discussion of the method applicability in the rebuttal is convinced for me. I upgrade my score to 7. This paper proposes a learning-based approach for combinatorial optimization problems. Starting from an initial complete solution of the problem, several local rewriting updates are applied to the solution iteratively. In each rewriting step, a local region and an updating rule are picked to update the solution and two networks are trained by reinforcement learning to pick local regions and updating rules.