• Unprofessional writing. - Most starkly, “policies” is misspelled in the title. • At times, information is not given in an easy-to-understand way. - E.G. lines 147 - 152, 284 - 289. • Captions of figures do not help elucidate what is going on in the figure. This problem is mitigated by the quality of the figures, but it still makes it much harder to understand the pipeline of LCP and its components. More emphasis on that pipeline would help with the understanding. • 100 nodes seem like a small maximum test size for TSP problems (though this is an educated guess). Many real-world problems have thousands or tens of thousands of nodes. • Increase in optimality is either not very significant, or not presented to highlight its significance. It would be better to put the improvement into perspective. • Blank spaces in table 1 are unclear. Opportunities:
• It would be good to describe why certain choices were made. For example, why is the REINFORCE algorithm used for training versus something like PPO? I presume it has to do with the attention model paper this one iterates on, but clarification would be good.
• More real-world uses of the algorithm could be included to better understand the societal impact, including details on how LCP could be integrated well.
The paper lacks a high degree of polish and professionalism, but its formatting (e.g. bolded inline subsubsections) and figures are its saving grace. The tables are also well structured, if a bit cluttered --- values are small and bolding is indistinct. This paper does a good job of giving this information and promises open source-code on publication.
Overall, the paper and its presentation have several problems, but the idea seems elegant and useful.
Yes. The authors have adequately addressed the limitations and potential negative societal impact of their work
• It would be good to describe why certain choices were made. For example, why is the REINFORCE algorithm used for training versus something like PPO? I presume it has to do with the attention model paper this one iterates on, but clarification would be good.