Review for NeurIPS paper: A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning

Weaknesses: - In multi-agent reinforcement learning research, Schelling diagrams are normally plotted as a function of the number of *other cooperators* (besides the focal agent making the decision), i.e. C - 1, rather than the total number of cooperators, C, as was done here. Either way is certainly correct in principle, Schelling said as much in the original 1973 paper. However, there are several reasons why the C - 1 parameterization is convenient. For instance, it lets you read off game theoretic properties from the diagram more easily. To see if cooperation or defection is favored for a particular number of other cooperators, you simply compare a point on the R_c curve to the point on the R_d curve that is right above it.